8/18/2019 Is resilience socially constructed? Empirical evidence from Fiji, Ghana, Sri Lanka, and Vietnam http://slidepdf.com/reader/full/is-resilience-socially-constructed-empirical-evidence-from-fiji-ghana-sri 1/18 Isresilience sociallyconstructed?EmpiricalevidencefromFiji,Ghana, SriLanka,andVietnam Christophe Béné a, *, Ramatu M. Al-Hassan b ,Oscar Amarasinghe c ,Patrick Fong d , Joseph Ocran h ,Edward Onumah b , Rusiata Ratuniata d , Truong Van Tuyen e , J. Allister McGregor a ,David J. Mills f ,g a Institute of Development Studies, University of Sussex, UK b Department of Agricultural Economics & Agribusiness University of Ghana-Legon,Ghana c Faculty of Agriculture, University of Ruhuna, Sri Lanka d Institute of Applied Science, Faculty of Science and Technology, University of the South Paci c, Fiji e Hue University of Agriculture and Forestry, Vietnam f WorldFish Center, Penang, Malaysia g ARC CoE for Coral Reef Studies, James Cook University, Townsville, Australia h Department of Sociology University of Ghana-Legon, Ghana AR TICL EINFO Articlehistory: Received5 June2015 Receivedinrevisedform17 January2016 Accepted9March2016 Availableonlinexxx Keywords: Resilience Shock Stressors Socialcapital Small-scalesheries ABSTR ACT The objective of this paper is to better understand the various individual and household factors that inuence resilience, that is, people’s ability to respond adequately to shocks and stressors. One of our hypotheses is that resilience does not simply reect the expected effects of quanti able factors such as level of assets, or even less quantia bl e s oc ia l p ro ce ss es s uc h a s p eo pl e ’s experience, but is also determined by more subjective dimensionsrelated to people’s perceptions of their ability to cope, adapt or transform in the face of adverse events. Data collected over two years in Fiji, Ghana, Sri Lanka and Vietnam conrmstheimportance ofwealthintherecoveryprocessofhouseholdsaffectedbyshocksand stressors. However our results challenge the idea that within communities, assets are a systematic differentiator in people ’ s response to adverse events.The ndingsregardingsocialcapitalaremixed and call formore research:socialcapitalhad astrongpositiveinuenceonresilienceatthecommunitylevel, yetouranalysisfailedto demonstrateanytangiblepositivecorrelationatthehouseholdlevel.Finally,the data conrm that, like vulnerability, resilience is at least in part socially constructed, endogenous to individual and groups, and hence contingent on knowledge, attitudes to risk, culture and subjectivity. ã 2016 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/ ). 1. Introduction Sincethe1980s, agrowingbodyof evidencehaspointedtothe debilitating impacts thatunexpectedchanges, shocksandextreme eventscanhaveonthelivesandwellbeingof poorpeoplein developing countries (Morduch, 1995;BaulchandHoddinott, 2000; Sinha et al., 2002; Yamano et al., 2003; Dercon et al., 2005; IPCC, 2012).Smalleventssuchasadelayinrainfall, individual illness, ormoresevereidiosyncratic orcovariateshockssuchasthe deathof thehouseholdhead, consecutiveharvestfailures, orthe devastatingimpactof seasonaltropical storms, canhaveirrevers- ibleconsequences onpeople’s lives,affectingtheirincome, food securityandhealth, andpossiblydrivingthemdeeperintopoverty. Inthiscontextbecauseitholdsparticular appealtotheideaof peoplebeingabletoendureshocksandstressorsandbounceback- resilience hasemergedasaconceptthatcouldhelpacademics and practitioners better understand the links between shocks, responses anddevelopment outcomes(Constasetal., 2014a). “Resilienceoffersalenswithwhichtoexplorestressorsandshocks andtounderstandlivelihooddynamics” (Marschke andBerkes, 2006,p.2). Assuchresiliencethinkingisnowbecomingacentral componentintheplanningandimplementation of interventions inmanysectorsincluding humanitarian activities (DFID, 2011), disasterriskreduction (Kleinetal.,2003),climatechange adaptation(Boydetal.,2008),socialprotection(WorldBank, 2011),andfoodsecurityandnutrition(vonGrebmeretal.,2013; Constas etal.,2014b). *Correspondingauthor. Currentaddress:International CenterforTropical Agriculture(CIAT), Km17, RectaCali-PalmiraApartadoAéreo6713Cali,Colombia. E-mailaddresses:[email protected](C.Béné), [email protected](R.M.Al-Hassan), [email protected](O.Amarasinghe), [email protected](P.Fong), [email protected](T.V.Tuyen), j.a.mcgregor@shef eld.ac.uk(J.A.McGregor), [email protected](D.J.Mills). http://dx.doi.org/10.1016/j.gloenvcha.2016.03.005 0959-3780/ ã 2016TheAuthors. PublishedbyElsevierLtd.ThisisanopenaccessarticleundertheCCBY-NC-NDlicense(http://creativecommons.org/licenses/by-nc-nd/4.0/ ). GlobalEnvironmental Change38(2016)153–170 ContentslistsavailableatScienceDirect GlobalEnvironmental Change journal homepage:www.elsevier.com/locate/gloenvcha
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8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
Christophe Beacuteneacutea Ramatu M Al-Hassanb Oscar Amarasinghec Patrick Fongd Joseph Ocranh Edward Onumahb Rusiata Ratuniatad Truong Van Tuyene J Allister McGregora David J Millsf g
a Institute of Development Studies University of Sussex UK bDepartment of Agricultural Economics amp Agribusiness University of Ghana-LegonGhanac Faculty of Agriculture University of Ruhuna Sri Lankad Institute of Applied Science Faculty of Science and Technology University of the South Paci 1047297c FijieHue University of Agriculture and Forestry Vietnamf WorldFish Center Penang Malaysiag ARC CoE for Coral Reef Studies James Cook University Townsville AustraliahDepartment of Sociology University of Ghana-Legon Ghana
A
R
T
I
C
L
E
I
N
F
O
Article history
Received 5 June 2015
Received in revised form 17 January 2016
Accepted 9 March 2016
Available online xxx
Keywords
Resilience
Shock
StressorsSocial capital
Small-scale 1047297sheries
A
B
S
T
R
A
C
T
The objective of this paper is to better understand the various individual and household factors that
in1047298uence resilience that is peoplersquos ability to respond adequately to shocks and stressors One of our
hypotheses is that resilience does not simply re1047298ect the expected effects of quanti1047297able factors such as
level of assets or even less quanti1047297able social processes such as peoplersquos experience but is also
determined bymore subjective dimensions related to peoplersquos perceptions of their ability to cope adapt
or transform in the face of adverse events Data collected over two years in Fiji Ghana Sri Lanka and
Vietnam con1047297rmstheimportance ofwealth in therecoveryprocess of householdsaffectedbyshocks and
stressors However our results challenge the idea that within communities assets are a systematic
differentiator in peoplersquos response to adverse eventsThe 1047297ndings regarding social capital aremixed and
call formore research social capitalhad a strongpositive in1047298uence on resilienceat thecommunitylevel
yetour analysis failedto demonstrate anytangible positive correlation at thehousehold levelFinallythe
data con1047297rm that like vulnerability resilience is at least in part socially constructed endogenous to
individual and groups and hence contingent on knowledge attitudes to risk culture and subjectivity
atilde 2016 The Authors Published by Elsevier Ltd This is an open access article under the CC BY-NC-ND
jamcgregorshef 1047297eldacuk (J A McGregor) DMillscgiarorg (DJ Mills)
httpdxdoiorg101016jgloenvcha201603005
0959-3780atilde2016 The Authors Published by Elsevier Ltd This is an open access article under the CC BY-NC-ND license (httpcreativecommonsorglicensesby-nc-nd40)
Global Environmental Change 38 (2016) 153ndash170
Contents
lists
available
at
ScienceDirect
Global
Environmental
Change
journa l home page wwwe lseviercomloca te gloenv cha
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
con1047297dence and the perception they had of their own ability to
restore their livelihood (Beacuteneacute et al 2015a) In these circumstances
it becomes as important to understand peoplersquos perceptions about
a particular event as it is to assess the actual objective impacts of
that particular event (Tansey and OrsquoRiordan 1999) The third key
hypothesis explored in this study was therefore that resilience is
subjectively constructed or at least is strongly in1047298uenced by social
and individual self-perception norms values and self-con1047297dence
in peoples ability to handle future events
3
Methods
and
data
31 Analytical framework
The last three to
1047297ve years have seen rapid progress in the
understanding of what (individual household community)
resilience is about supported by a growing body of primary and
grey literature see Frankenberger and Nelson (2013) for a recent
review Drawing on this literature we developed an analytical
framework to clarify the types of information needed to assess
peoplersquos resilience This framework which is shown on Fig 1
includes four main components (i) a shock and stressor inventory
and their impacts (ii) a household characteristics and wellbeing
assessment (iii) a householdsrsquo response typology and (iv) anoutcome analysis
Information was collected at both household and community
levels on the nature intensity and characteristics (frequency
duration date of occurrence) of the various shocks and stressors
experienced (idiosyncratic and co-variant events) The stochastic
characteristics of these events were expected to in1047298uence the type
of responses employed Accordingly a distinction was made
between three types of events (i) rapid shocks de1047297ned as short
and unpredictable adverse events affecting the lives andor
livelihoods of one or more members of the household (ii)
medium-term stressors de1047297ned as adverse events that last several
months andor occur recurrently and (iii) long-term trends that
occur graduallyincrementally and have potentially negative (or
positive) effect on peoples lives and livelihoodsThe household characteristics and wellbeing analysis covered
demographics and resource base (level of education age and
gender of the head size of the household etc) and socio-
economic status (economic wealth number and nature of income-
generating activities etc) Wealth was proxied by the level of
household assets as questionnaire-based assessment of household
income is notoriously unreliable and often provides an incomplete
picture of wealth (Morris et al 2000) In addition to these more
conventional variables data on ten domains of quality of life were
collected to capture and re1047298ect the multiple dimensions that are
considered to affect the wellbeing of households These ten
domains were collected because these dimensions and the level of
satisfaction that people experience in relation to them were
thought to be important factors in1047298uencing peoplersquos perception of
their ability to handle shocksstressors The analysis was therefore
expected to illuminate in greater detail what might be driving the
choice of the strategies that households make in an effort to
respond to shocksstressors The various types of responses to
shocks and stressors adopted by households were recorded and
coded into four main categories based on commonalities in
responses among households across the four countries (see
below)
Finally our framework was based on the premise that the
ultimate outcomes (general wellbeing food security or nutrition
status of a household) following an adverse event do not merely
result from the direct impact of that initial shock (eg destruction
of assets losses of livestock physical injuries) but instead are the
result of that shockrsquos impact combined with the responses
employed by individualshouseholds or communities to counter-act that shock as illustrated in Fig 1 To use a concrete example
when a household decides to send their eldest son to the capital
city following the loss of the latest harvest (or in our case say the
loss of 1047297shing gear) due to a strong tropical storm the ultimate
outcomes of this event is not merely the impact of the storm and
subsequent loss of 1047297shing gear but rather is the combination of
that impact with the consequences of the response put in place by
the household (sending the son away) A neighbour in the same
community who would have experienced the exact same event
(loss of 1047297shing gear due to the same tropical storm) might have
decided to respond differently (say by borrowing money) The
outcome for this second household will be different even though
exposed to the same initial shock
32 Data collection and statistical analyses
In the four focus countries Fiji (Paci1047297c) Vietnam and Sri Lanka
(Asia) and Ghana (Africa) small-scale
1047297sheries are known to be
an important basis for livelihoods in a large number of coastal
Fig 1 The analytical framework used for this resilience analysis made of four components (i) a shock and stressor inventory (ii) an household characteristics and wellbeing
assessment (iii) a response typology and (iv) an outcome analysis where the ultimate outcome is measured in terms of change in household wellbeing (eg food security or
nutrition for the justi1047297cation of this see Constas et al 2014b or Beacuteneacute et al 2015b) Note that as an analytical tool this framework is not intended to represent the full suite of
processes
and
feedback
loops
that
are
associated
with
learning
C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170 155
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
when all events are aggregated households are hit by a new event
of some kind every 485 days that is every 16 months
42 Household response analysis
The next step was to document and analyse the various types of
strategies that households employed in the face of shocks and
stressors In the resilience analysis framework (Fig 1) this
corresponds to the
lsquoresponse analysisrsquo component
Fig 4 presents the event-response matrices for the four country
case studies (computed for the ten most cited events per country)
The colour codes correspond to the four categories described in
Table 1 coping strategies social-relation based strategies 1047297shery-
related strategies and non-1047297shery-related strategies
The matrices show that coping strategies are the most frequent
responses put in place by households Amongst coping strategies
reduction of food consumption and reduction of general expenses
were commonly adopted while asset selling was notable for being
seldom adopted except in Ghana Beyond the generic pattern of
0 005 01 015 02 025 03 035
Others
High de
Destruconlossthe of fishing gear
Sudden change in sea condion
Slow increase in input prices
Major health problem
Death
Flood
Rapid (peak) increase in input prices
Decline in fish price
Sudden decli ne in catch
Slow decline in catch
Slow increase in food prices
Important change in fishing techniques
Any other fishery rela ted issue
unpredictable c hanges in weather
Hurricane
Percentage (total = 100)
Fiji
ST
MT
LT
0 005 01 015 02 025 03
Others
Increase in Food Price
Storm and strong winds
Unpred weather change
Accident Disability
Change in sea condion
Loss of financial assets
Loss of other assetsLoss fishing ground
Flood
Fish price increase
Sick family member
Death of family member
Destrucon The Loss gear
Input prices increase
Change in fishing techniques
Fuel shortage
Slow decline in catch
Percentage (total = 100)
Ghana
ST
MT
LT
0 005 01 015 0
Others
Slow but constant increase in input prices
Death of a family m ember
Other major weather event
Sudden change in sea condion
Flood
Sudden decline in catch
Loss of other assets other than fishing gear
Major health problem (sickness)
Decline in fish price
More unpredictable changes in weather paern
Important change in fishing techniquesSlow decline in catch
Limitaons-Harbour
New constraining fishing regulaon
Destruconlossthe of fishing gear
Rapid (peak) increase in input prices
Hurricane tropical storm
Perccentage (total = 100)
Sri Lanka
ST
MT
LT
0
005
01
015
02
025
03
035
04
045
Others
Lost assets
Accident
Erosion
Catch r educed suddently
Gears lost
Cold wind prolongs
Typhoon
Illness
Food price increase
Input price increa se connuously
Big boats compete ground and catch
Catch reduced connuously
Percentage (total = 100)
Vietnam
ST
MT
LT
Fig 2 Adverse event inventory for the four countries Events have been grouped and colour-coded into three categories short and unpredictable shocks (ST) (ii) medium-
term stressors that last several months andor are recurrent (MT) and (iii) long-term trends (LT)
0 10 20 30
Annually
On a connuous (daily) basis
Every 5 years
Bi-annually
Quarterly basis
Weekly basis
Monthly basis
Every two-year
Every 10 years
Every 20 year or less oen
Percentage of responses (total = 100)
(c) Event frequency
0
10
20
30
40
50
60
70
1 2 3 4 5
P e r c e n t a g e o f r e s p o n s e s ( t o t a l = 1 0 0 )
5-point scale rang
(b) Event severity
very bad lt ---------------------------------- gt posive
0
10
20
30
40
1 2 3 4 5
P e r c e n t a g e o f r e s p o n s e s ( t o t a l = 1 0 0 )
Fig 4 Event-response matrices for the four country case studies The numbers in the column are percentage of total responses ranked from the most (left) to the least (right)
adopted
and
colour-coded
using
the
typology
presented
in
Table
1 Full
details
are
provided
in
Appendix
A
Table 4
Average number of responses per event at the community level
Country Community Mean Std Err [95 Conf Interval]
Fiji A 27 022 232 317
B 26 007 244 272
Ghana C 43 018 389 461
D 39 016 359 421
Sri
Lanka
E
55
020
514
594F 76 026 707 809
Vietnam G 34 012 319 367
H 35 019 308 383
Total
(N
=
1868)
46
005
451
474
C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170 159
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
Resilience outcomes were explored using psychometric tech-
niques where households were asked to self-assess the degree of
recovery they managed to achieve for each of the adverse events
they had experienced in the past (see details in Table 2) The
answers provided by the respondents to the 1047297rst two questions of
the resilience analysis (self-recovery from past event and self-
recovery compared to the rest of the community) were used to
create a resilience index (RI) computed as the product of the two
scores As a result of the calculation process RI is an integer varying
between 1 and 30 where low values indicate low level of resilienceto a speci1047297c event while higher values indicate higher levels of
resilience
We then used this resilience index to explore the last remaining
working hypothesis of this research that is that
lsquosocial capital is
importantrsquo- ie the (intuitive) idea that households or communi-
ties characterized by higher level of social capital are able to draw
on social capital to help themselves (and others) in the aftermath
of an adverse event To analyse the resilience outcomes and explore
in particular this last hypothesis a three-level mixed effect linear
model was run where the resilience index was tested against a
series of 1047297xed and random factors used as independent explana-
tory variables Because the communities are nested within the
countries a three-level (hierarchical) model was
1047297tted with
random intercepts at both country and community-within-
country levels Random coef 1047297cients were also accounted for at
the country level on the Quality of Life (QoL) factors to re1047298ect
country speci1047297c effects More speci1047297cally the model was of the
form
RI vc frac14 b0 thorn b1Shockvc thorn b2Respvc thorn b3QoLvc thorn b4HH vc thorn g 1W c thorn g 2 Z vc thorn
evc
where the subscripts v and c hold for village (community) and
country respectively Shockvc is the covariate matrix for the
1047297xed
effect
b1 of the impacts of event e on individual household Respvc
is the covariate matrix for the 1047297xed effect b2 of the responses put in
places by the household QoLe is the covariate matrix for the
1047297xed
effect b3 of the Quality of Life scores recorded for each household
HH e is the matrix of variables and dummies controlling for
household characteristics W c is the covariate matrix for the cluster
random effect at the country level and Z vc is the covariate matrix
for the cluster random effect at the community level The details of
the different categories of variables included in the model are
provided in Table 6
Results of the model estimations including details of both
1047297xed and random effect speci1047297cations and diagnostic checking-
are presented in Table 7 The model highlights a series of important
1047297ndings First the degree of severity of the shock and the
disruptive impact on income are the twoshock variables that have
0
10
20
30
40
50
60
70
80
90
F o o d
E x p e n s e s
M o n e y
A s s e s t
S u p p o r t
C o l l a b o r a o n
D i v e r s i fi c a o n
M i g r a o n
E x i t
C h a n g e
I n c r e a s e
P e r c e n t a g e o f h o u s e h o l d s ( )
Response typology (Vietnam)
Boom 40
Top 40
0
01
02
03
04
05
06
07
F o o d
E x p e n s e s
M o n e y
A s s e t s
S u p p o r t
C o l l a b o r a o n
D i v e r s i fi c a o n
M i g r a o n
E x i t
C h a n g e
I n c r e a s e
P e r c e n t a g e o f h o u s e h o l d s ( )
Response typology (Fiji)Boom 40
Top 40
Fig 5 Comparative analysis of the responses adopted by the bottom (poorest) and top (wealthiest) 40 of the households when affected by the same event illustration
from Vietnam and Fiji Code of the responses
ldquoFoodrdquo = Reduce food consumption
ldquoExpensesrdquo = Reduce family general expenses
ldquoMoneyrdquo = Borrow money
ldquoAssetsrdquo = Sell
family assets
ldquoSupportrdquo= Seek for support from friends and peers
ldquoCollaborationrdquo= Develop new collaboration within the community
ldquoDiversi1047297cationrdquo = Invest in non-
1047297shery activities ldquoMigrationrdquo = Temporary permanently migration one or several members of the family ldquoExitrdquo = Exit the 1047297shery start a new joblivelihoodldquoChangerdquo = Change 1047297shing strategies
ldquoIncreaserdquo = Increase 1047297shing effort
160 C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
The type of responses adopted by households was included in
the model to test whether the level of resilience of households is
effectively in1047298uenced by those responses Amongst the 11 types of
responses tested three have statistically signi1047297cant signs engag-
ing
in
new
collaboration
(negative
sign
P
=
0001)
increasing1047297shing effort (positive P lt 00001) and quitting the
1047297shery
(negative P = 0047) The negative correlation found between
household resilience and the strategy that consists of forming new
collaboration may be dif 1047297cult to interpret as it can re1047298ect many
highly contextual factors The two others responses and the signs
of their correlations (one negative sign for leaving the sector and
one positive sign for increasing 1047297shing effort) are initially
disturbing but eventually not too surprising Disturbing
1047297rst
because this
1047297nding does not lead to the type of long-term
behaviours that appeal to policy makers and 1047297shery managers On
the contrary they would rather see 1047297shing effort reductions and
exit strategies more often adopted by
1047297shers in particular in the
context of the current world
1047297shery crisis Not surprising however
because this result is in line with what one could expect from
1047297sherfolks after an adverse event in the face of a long-term stress
(such
as
the
drop
in
income
following
a
continuous
decline
in
1047297shcatch) or a sudden need for cashrevenues (as a consequence of
eg destruction of 1047297shing gear induced by bad weather or the
need to pay health bills)
1047297shers are often observed to alter their
1047297shing activities to make up for these events usually by changing
adjusting their 1047297shing strategy (eg switching between targeted
species andor
1047297shing gear) or increasing their
1047297shing effort (eg
investing in more ef 1047297cient
1047297shing gear increasing the quantity of
gear used or increasing the number of days at sea) in an attempt to
generate more cash In that context it is not surprising that the
majority of 1047297shing households interviewed in this research
consider that their ability to
lsquobounce back following an adverse
event was enhanced when they increase their 1047297shing effort
Additionally given what we know about their strong sense of
identity
(Kelty
and
Kelty
2011
Trimble
and
Johnson
2013) but
alsothe importance of peer-pressure and reputation (see eg Beacuteneacute and
Tew1047297k 2001) quitting the 1047297shery would certainly be perceived by
many 1047297shers as a failure thus the negative correlation between
(perceived) resilience and leaving the sector
The next category of variables which was investigated through
the model was the Quality of Life indicators (see Table 3 for a
recall) A reasonable hypothesis although not explicitly formu-
lated in the
lsquoworking hypotheses section above- is that some of
these QoL indices may have a positive effect on the ability of
households to handle and recover from adverse events One can
indeed assume that households satis1047297ed in many of the
dimensions of wellbeing which they considers important (such
as say access to health services or to public infrastructure) may
feel better equipped to reactrespond to any particular event than
Table 5
Top comparison of propensities to adopt particular types of responses for households characterized by high (N = 224) and low (N = 235) subjective resilience Bottom
comparison of the two same groups in terms of asset levels education and age of the household head
Responses subjective
resilience
level
Mean [95 Conf
Interval]
test resulta
Coping strategies High 198 1840 2136 t = 43037 Pr(|T| gt |
t|) = 0000
Low 245 2311 2596
Social-relation-based strategies High 083 0738 0927 t = 05187 Pr(|T| gt |
t|) = 0604
Low 086 0787 0943
Fishing-related strategies High 083 0732 0935 t = 03267 Pr(|T| gt |
t|)
=
0744
Low 081 0715 0906
Non-1047297shery
strategies
High
067
0559
0794
t
=
35599
Pr(|T|
gt
|
t|) = 0000
Low 042 0341 0502
Household characteristics
Asset High 768 7218 8157 t = 08882 Pr(|T| gt |
t|) = 0374
Low 739 6938 7848
Education High 796 7338 8599 t = 10186 Pr(|T| gt |
t|)
=
0308
Low 750 6857 8147
Age High 4688 45377 48391 t = 01332 Pr(|T| gt |
t|) = 0894
Low 4702 45570 48482
p
lt 5
p
lt 1
p
lt 1
a mean difference unpaired t -test Ho Diff = 0 Ha diff 6frac14 0
C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170 161
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
diversif non 1047297sher diversi1047297cation dummy 1 = yes
exit_1047297sh exit the 1047297shery sector dummy 1 = yes
migrat migrate dummy 1 = yes
quality of life indices
index_incom
income
index
ordinal
variable
coded
[-6
+6]
ndash6
=
very
poor
+6
=
very
strong
index_livelih livelihood index ordinal variable coded [-6 +6] ndash6 = very poor +6 = very strongindex_housing housing and infrastructure index ordinal variable coded [-6 +6] ndash6 = very poor +6 = very strong
index_educ education index ordinal variable coded [-6 +6]
ndash6 = very poor +6 = very strong
index_soc social capital index ordinal variable coded [-6 +6]
ndash6 = very poor +6 = very strong
index_health health index ordinal variable coded [-6 +6] ndash6 = very poor +6 = very strong
ind_emp empowerment index ordinal variable coded [-6 +6]
ndash6 = very poor +6 = very strong
index_soc_cris social capital index in time of crisis
ndash6 = very poor +6 = very strong
index_emp_cris empowerment index in time of crisis
ndash6 = very poor +6 = very strong
index_spirit index of spirituality
ordinal variable coded [-6 +6]
ndash6 = very poor +6 = very strong
household characteristics
HH head sex sex of household head dummy 1 = female
HH
head
age
age
of
household
head
age
in
years
HH head educ level of education of the household head 0 = no education 20 = post-graduate level
HH size size of household number of members (not adjusted for age)
log_asset household assets (log-transformed) value of household assets (proxy for wealth level)
community
resiliencecomm_recov level of recovery of the community
a Fitting a three level model requires two random-effect equations one for level three (country) and one for level two (community) with i = 1 nvc 1047297rst level of
observation (households) nested within k = 1 8 s level cluster (community) nested within j = 1 4 third level cluster (country)
162 C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
community level in the same way than the QoL indices that is by
averaging the scores obtained at the individual household level)
The best correlation was obtained with the QoL index of social
capital in time of crisis (R 2= 077 F = 0004) see Fig 6- suggesting
that communities with higher social capital in time of crisis are
also characterized by higher level of resilience
5 Discussion
Resilience has been increasingly recognized as a potentially
useful concept to help practitioners academics and policy-makers
better understand the links between shocks response and longer-
term development outcomes (Constas et al 2014a Beacuteneacute et al
2014) Incorporating resilience alongside vulnerability analysis can
contribute an essential element to societal ability to better prepare
for future shocks and stressors This paper argues that improving
our understanding of what contributes to or constitutes peoplersquos
resilience requires not only the development and
1047297eld-testing of
robust and measurable indices (Beacuteneacute 2013 Constas et al 2014b)
but also a better insight into the social factors including
knowledge perceptions and motivations- that in1047298uence and affect
individual and collective capacity to respond to shocks and
stressors
Our analysis conducted in eight 1047297shery-dependent communi-
ties from Fiji Ghana Sri Lanka and Vietnam reveals a series of
notable results in relation to these questions In considering these
outcomes it is important to 1047297rst take stock of potential limitations
pitfalls or biases in the study methodology Given the nature of the
1047297ndings two potential issues require further consideration First is
the question of how representative our sampling methodology
was It could be argued for instance that the observed low adoption
rates of non-1047297shery strategiesndash and in particular the low score of
the
lsquoexiting the
1047297sheryrsquo was driven by our sampling method
underrepresenting these groups as those who had effectively left
the 1047297shery were not included in the sample
The FGDs that preceded the household survey speci1047297cally
addressed this issue In Sri Lanka for instance the opening question
prompted participants (both men and women) to discuss whether
ldquo1047297shers in their community had ever left 1047297sheries due to their
inability to cope with adverse eventsrdquo The answer was that it
generally does not happen with the notable exception of someyoung
1047297shers who attempted to migrate to Australia through
illegal means If it occurred exiting the 1047297shery was said to be
temporary ldquothey may leave the village or 1047297shing but will come
back when the situation is favourablerdquo In Vietnam the sampling
was speci1047297cally designed to cover both
1047297shers and ex-1047297shers in
proportions represented in the community As a result 9 ex-1047297shers
were included in the sample Overall therefore although we were
unable to conceive of a completely representative sampling design
(in the statistical sense) the parallel information that was collected
in the FGDs and the individual households converge to suggest that
exiting the
1047297shery was not an option envisaged by the members of
these different communities and consequently that our sampling
was not too severely biased
0
2
4
6
8
10
12
14
16
-05 05 15 25
C o m m u n i t y l e v e l r e s i l i
e n c e i n d e x
Community level social capital in me of crisis
Fiji
Ghana
Sri Lanka
Vietnam
Fig 6 Correlation between social capital in time of crisis and resilience index
across the eight communities The straight line represents the linear relation
(R 2 = 077 F = 0004) and the bars are 95 con1047297dence intervals for each community
Random-effects parameters St Dev Std Err [95 Conf Interval]
country level
index_incom 043 024 0146 1266
index_livelih 051 027 0175 1464
index_housing 013 013 0018 0962
index_soc 039 024 0119 1303
index_soc_cris
078
038
0300
2009index_educ 015 013 0028 0834
const 090 067 0209 3861
community level
const 032 026 0066 1534
residuals 277 008 2617 2923
LR test vs linear regression chi2(7) = 3916 Prob gt chi2= 0000
p
lt 5
p
lt
1 p lt 1ma Fitting a three level model requires two random-effect equations one for level three (country) and one for level two (community) with i = 1 nvc 1047297rst level of
observation
(households)
nested
within
k
=
1
8
second
level
cluster
(community)
nested
within
j
=
1
4
third
level
cluster
(country)b The likelihood-ratio (LR) test comparing the nested mixed-effects model with the corresponding 1047297xed effect model con1047297rms the appropriate use of the mixed effect
model (chi2(7) = 3916 Prob gt chi2= 0000) and the Wald test con1047297rms that the independent variables are valid predictors (Wald chi2(45) = 59414 Prob gt chi2= 0000) A
speci1047297cation test performed on the 1047297xed effect model using a Pregibonrsquos goodness-of-link test shows good results (t = 077 P gt |t| = 0439)
c The dummy variables sev_event3 cat_event2 predict2 and comm_recov3 were omitted from the 1047297xed effect component for estimation purpose
Table 7 (Continued)
164 C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
The second potential limitation in our methodology relates to
the way the level of resilience of the households was assessed
While psychometric measurements are reliable and their results
replicable and testable when correctly implemented (Vigderhous
1977) one could fear that their use in the speci1047297c case of resilience
measurement could be subject to the effect of adaptive preference
that is the deliberate or re1047298exive process by which people adjust
their expectations and aspirations when trying to cope with
deterioration in living conditions (see eg Nussbaum 2001 Teschl
and Comim 2005) In our case this means that households
undergoing a degree of adaptive preference could have over-
estimated their ability to recover Although this risk is present we
tried to mitigate (or to reduce) it by introducing a qualifying
element in each of the coded answers of the resilience question-
naire so that respondents would have to associate the
1047297rst part of
their answer ldquoI have fully recoveredrdquo with a particular lsquoframe of
reference or quali1047297er (eg ldquoand it was not too dif 1047297cultrdquo) This frame
determined how they comprehend the questions being asked and
reduced the risk of the respondent simply relying on emotional
elements to answer these questions
Keeping in mind these potential limitations we now turn to
what we consider the most notable results of this research First is
the
lsquocumulative and continuous effect of shocks and stressors
whereby the impacts and disturbance of sequential shocksstressors and trends during the last 1047297ve years combine and
coalesce to create a constant non-stop stress We saw that the
nature and the source of events that were identi1047297ed by the
respondents in the four countries are all highly varied and
composite and reveal no speci1047297c clear pattern The events are a
combination of idiosyncratic and covariant sudden shocks and
long-term continuous trends Some are predictable while others
are totally unexpected All affect households simultaneously and
on an almost continuous basis The data suggests in particular that
on average households are hit by a new event every 16 months
This result calls into questions the framework generally used to
conduct shock or vulnerability assessment Often the approach has
been to disaggregate the problems people face and focus on single
threats such as eg 1047298ood or increase in food prices in order todevelop a clearer understanding of the impact of these particular
shocks and the ways people respond to them This approach has
been challenged however by a growing number of scholars who
argue that the reality households face on a daily basis is not linear
and mono-dimensional (OrsquoBrien and Leichenko 2000 Eriksen and
Silva 2009 Quinn et al 2011 McGregor 2011) Instead they argue
risks and vulnerability are often the product of multiple stressors
(Turner et al 2003 OrsquoBrien et al 2009) where social economic
political and biophysical factors interact combine and reinforce
each other to create a complex and dynamic multi-stressor multi-
shock environment (Reid and Vogel 2006 Adger 2006) Our
results corroborate this new interpretation
In line with this our analysis also shows that most households
engage in a suite of responses to a given shock On average
households adopted more than 4 types of responses to a particular
event This last result does not simply imply a rethinking of the way
shock or vulnerability assessments are conceptualized and
conducted see eg Turner et al (2003) or Leichenko and OrsquoBrien
(2008) It also demonstrates that the mental model (shock
gt response gt recovery) which is widely accepted in the
resilience literature is too simplistic and possibly misleading in
the sense that a state of (full) recovery may not exist This is at least
what was observed for the households included in our research
these households did not seem to have the chance or the time to
fully recover from one particular event before being affected by the
next Instead they were caught in what we could characterize as ldquoaconstant state of incomplete recoveringrdquo from new shocks and
stressors as illustrated in Fig 7
The next entry point in this discussion is wealth Our mixed
effect model (Table 7) shows that wealth was positively correlated
with household resilience Wealth has been identi1047297ed in the
literature as a key factor in strengthening the resilience of
households (Prowse and Scott 2008 WFP 2013) Analysis of
rural Ethiopian households hit by drought for instance showed that
while better-off households could sell livestock to smooth
consumption the poorer often tried to hold on to their livestock
at the expense of food consumption to preserve their options for
rebuilding herds The same study also shows that in the aftermath
of the hurricane Mitch in Honduras the relatively wealthy
households were able to rebuild their lost assets faster than thepoorest households for whom the effects of the hurricane were of
longer duration and felt much more acutely (Carter et al 2007) In
Fig 7 Left Current conceptualisation of resilience shock gt response gt recovery as presented in the literature [here redrawn from Carter et al 2007] Right actual
situation where the multi-stressor multi-shock environment induces that households are in a trajectory of continual and incomplete recovery Not represented here are the
multi-response
strategies
put
in
place
by
households
to
respond
to
these
adverse
events
C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170 165
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
disaster resilience National Disaster Resilience Roundtable Report 20September 2012 Melbourne Australia 36 p
Adger NW Dessai S Goulden M Hulme M Lorenzoni I Nelson DR Naess LO Wolf J Wreford A 2009 Are there social limits to adaptation to climatechange
Clim
Change
93
335ndash354Adger WN 2003 Social capital collective action and adaptation to climate
change Econ Geogr 79 (4) 387ndash404Adger WN 2006 Vulnerability Glob Environ Change 16 268ndash281Aldrich D 2010 Fixing recovery social capital in post-Crisis resilience J Homeland
Secur 6 1ndash10Ayers
J
Forsyth
T
2009
Community-based
adaptation
to
climate
changestrengthening resilience through development Environment 51 23ndash31
Beacuteneacute C Tew1047297k A 2001 Fishing effort allocation and 1047297shermenrsquos decision-makingprocess in a multi-species small-scale 1047297shery analysis of the conch and lobster1047297shery in Turks and Caicos Islands Hum Ecol 29 (2) 157ndash186
Beacuteneacute
C
Evans
L
Mills
D
Ovie
S
Raji
A
Ta1047297da
A
Kodio
A
Sinaba
F
Morand
PLemoalle J Andrew N 2011 Testing resilience thinking in a poverty contextexperience from the Niger river basin Glob Environ Change 21 (4) 1173ndash1184
Beacuteneacute C Godfrey-Wood R Newsham A Davies M2012 Resilience new utopia ornew tyranny
ndash Re1047298ection about the potentials and limits of the concept of
resilience
in
relation
to
vulnerability
reduction
programmes
IDS
Working
Paperno 405 Institute of Development Studies Brighton 61 p
Beacuteneacute C Newsham A Davies M Ulrichs M Godfrey-Wood R 2014 Resiliencepoverty and development J Int Dev 26 598ndash623
Beacuteneacute C Waid J Jackson-deGraffenried M Begum A Chowdhury M Skarin VRahman A Islam N Mamnun N Mainuddin K Shah MA 2015a Impact of climate-related
shocks
and
stresses
on
nutrition
and
food
security
in
ruralBangladesh Dhaka World Food Programme 119 p
Beacuteneacute C Frankenberger T Nelson S 2015b Design monitoring and evaluation of resilience interventions conceptual and empirical considerations IDS WorkingPaper no459 Institute of Development Studies 23 p
Beacuteneacute
C
2013
Towards
a
quanti1047297able
measure
of
resilience
IDS
Working
Paper
434Institute of Development Studies Brighton 27 p
Bandura A 1977 Self-ef 1047297cacy toward a unifying theory of behavioral changePsychol Rev 84 191ndash215
Baulch R Hoddinott J 2000 Economic mobility and poverty dynamics indeveloping countries J Dev Stud 36 (6) 1ndash23
Belhabib
D
Sumaila
UR
Pauly
D
2015
Feeding
the
poor
contribution
of
WestAfrican 1047297sheries to employment and food security Ocean Coast Manage 11172ndash81
Berkes F Folke C 1998 Linking social and ecological systems for resilience andsustainability In Berkes F Folke C (Eds) Linking Social and EcologicalSystems Management Practices and Social Mechanisms for Building ResilienceCambridge University Press Cambridge pp 1ndash25
Bernier Q Meinzen-Dick R 2014 Resilience and social capital Building Resiliencefor Food and Nutrition Security Conference Paper No 4 International FoodPolicy Research Institute Washington DC 26 p
Bhattamishra R Barrett C 2010 Community-Based risk managementarrangements a review World Dev 38 (7) 923ndash932
Boarini R Kolev A McGregor JA 2014 Measuring well-being and progress incountries at different stages of development towards a more universalconceptual framework OECD Working Paper No 235 Organisation forEconomic Co-operation and Development Development Center
ndash Better Life
Initiative Paris 59 p
Boyd E Osbahr H Ericksen P Tompkins E Carmen Lemos M Miller F 2008Resilience and
lsquoclimatizingrsquo development examples and policy implicationsDevelopment 51 390ndash396
Cam1047297eld
L
McGregor
JA
2005
Resilience
and
wellbeing
in
developing
countriesIn Ungar M (Ed) Handbook for Working with Children and Youth Pathwaysto Resilience Across Cultures and Contexts Sage Publications Thousand OaksCA
Cam1047297eld
L
Ruta
D
2007
Translation
is
not
enough
using
the
Global
PersonGenerated Index (GPGI) to assess individual quality of life in BangladeshThailand and Ethiopia Qual Life 16 (6) 1039ndash1051
Carter M Little P Mogues T Negatu W 2007 Poverty traps and natural disastersin Ethiopia and Honduras World Dev 35 (5) 835ndash856
Cleaver
F
2005
The
inequality
of
social
capital
and
the
reproduction
of
chronicpoverty World Dev 33 (6) 893ndash906
Constas M Frankenberger T Hoddinott J 2014a Resilience measurementprinciples toward an agenda for measurement design Resilience MeasurementTechnical Working Group Technical Series No 1 Food Security informationNetwork Rome
Constas MT Frankenberger J Hoddinott N Mock D Romano C Beacuteneacute DMaxwell 2014b A common analytical model for resilience measurementcausal framework and methodological options Food Security InformationNetwork (FSIN) Technical Series No 2 World Food Programme Rome
Coulthard S 2011 More than just access to 1047297sh the pros and cons of 1047297sherparticipation
in
a
customary
marine
tenure
(Padu)
system
under
pressure
MarPolicy 35 405ndash412
DFID 2011 De1047297ning Disaster Resilience A DFID Approach Paper Department forInternational Development London pp 20
Dercon S Hoddinott J Woldehanna T 2005 Shocks and consumption in 15ethiopian
villages
1999ndash2004
J
Afr
Econ
14
(4)
559ndash585Dercon S 1996 Risk crop choice and savings evidence from Tanzania Econ Dev
Cult Change 44 (3) 485ndash513Duit A Galaz V Eckerberg K 2010 Governance complexity and resilience Glob
Environ Change 20 (3) 363ndash368Eriksen
SEH
Silva
JA
2009
The
vulnerability
context
of
a
savannah
area
inMozambique household drought coping strategies and responses to economicchange Environ Sci Policy 12 (1) 33ndash52
Fafchamps M Lund S 2003 Risk-Sharing networks in rural Philippines J DevEcon 71 (2) 261ndash287
Frankenberger T Nelson S 2013 Background Paper for the Expert Consultation onResilience
Measurement
for
Food
Security
TANGO
International
Rome
Foodand Agricultural Organization and World Food Program
Heltberg R Siegel PS Jorgensen SL 2009 Addressing human vulnerability toclimate change towards a
lsquono-regretsrsquo approach Glob Environ Change 19 89ndash99
Hoddinott
J
Dercon
S
Krishnan
P
2009
Networks
and
informal
mutual
supportin 15 ethiopian villages a description In Kirsten JF Dorward AR Poulton CVink N (Eds) Institutional Economics Perspectives on African AgriculturalDevelopment International Food Policy Research Institute Washington DC pp273ndash286
Hoddinott
J
2006
Shocks
and
their
consequences
across
and
within
households
inRural Zimbabwe J Dev Stud 42 (2) 301ndash321
Intergovernmental Panel on Climate Change (IPCC) 2012 In Field CB Barros VStocker TF Qin D Dokken DJ Ebi KL Mastrandrea MD Mach KJPlattner G-K Allen SK Tignor MMidgley PM (Eds) Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation A SpecialReport of Working Groups I and II of the Intergovernmental Panel on ClimateChange Cambridge University Press Cambridge UK
Jackson T 2005 Motivating sustainable consumptionmdasha review of evidence onconsumer behaviour and behavioural change A Report to the Sustainable
Event type (Vietnam) Reduce
expenditures
Borrow
money
Reduce
Food
Change
1047297shing
strategy
Get
support
Increase
1047297shing
effort
Diversi1047297cation Seek new
collaboration
Migration Exit the
1047297shery
Sell
assets
Total
Others (aggregated) 4 7 4 6 3 0 1 3 0 0 2 30
Erosion 2 4 2 1 6 2 2 2 3 1 25
Catch reduced
suddenly
8 4 6 7 1 2 4 2 34
Gears lost 10 18 6 5 1 2 1 43
Cold wind prolongs 15 7 11 3 1 7 2 46
Typhoon
12
11
10
2
4
2
3
5
4
1
1
55
Illness
11 14
6
2
11
2
2
4
1
1
2
56Food price increase 20 17 19 2 8 5 1 72
Input price increase
continuously
47 39 33 21 40 5 6 16 1 208
Big boats compete
ground and catch
54 39 32 40 9 19 11 15 8 3 2 232
Catch
reduced
continuously
102
70
80
63
22
51
51
25
23
17
6
510
Total 285 230 209 152 105 91 87 75 39 23 15 1311
C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170 169
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
Development Research Network Centre for Environmental StrategiesUniversity of Surrey
Jones L Boyd E 2011 Exploring social barriers to adaptation insights fromWestern Nepal Glob Environ Change 21 (4) 1262ndash1274
Kallstrom HN Ljung M 2005 Social sustainability and collaborative learningAmbio 34 376ndash382
Kelty R Kelty R 2011 Human dimensions of a 1047297shery at a crossroads resourcevaluation identity and way of life in a seasonal 1047297shing community Soc NatResour
24
(4)
334ndash348Klein RJT Nicholls RJ Thomalla F 2003 Resilience to natural hazards how
useful is this concept Environ Hazards 5 35ndash45
Krosnick
JA
Fabrigar
LR
1997
Designing
rating
scales
for
effective
measurementin surveys In Lyberg L Biemer P Collins M de Leeuw E Dippo C SchwarzN
Trewin
D
(Eds)
Survey
Measurement
and
Process
Quality
John
Wiley
andSons Inc New York NY pp 141ndash164
Leichenko R OrsquoBrien K 2008 Environmental Change and Globalization DoubleExposures Oxford University Press New York
Marschke M Berkes F 2006 Exploring Strategies that build livelihood resiliencea case from Cambodia Ecol Soc 11 (1) httpwwwecologyandsocietyorgvol11iss1art42
McGregor JA Cam1047297eld L Woodcock A 2009 Needs wants and goals wellbeingquality
of
life
and
public
policy
Appl
Res
Qual
Life
4
135ndash154McGregor JA 1994 Village credit and the reproduction of poverty in rural
Bangladesh In Acheson J (Ed) Economic Anthropology and the NewInstitutional Economics University Press of AmericaSociety for EconomicAnthropology Washington pp 261ndash281 (Chapter)
McGregor
JA
2011
Reimagining
development
through
the
crisis
watch
initiative
IDS Bull 42 (5) 17ndash23McLaughlin P Dietz T 2007 Structureagency and environment toward an
integrated perspective on vulnerability Glob Environ Change 39 (4) 99ndash111Meyer MA 2013 Social capital and resilience in the context of disaster social
capital
and
collective
ef 1047297cacy
for
disaster
resilience
connecting
individualswith communities and vulnerability with resilience in hurricane-pronecommunities in Florida PhD Dissertation Department of sociology Coloradostate University Fort Collins Colorado (311 p)
Mills DJ Adhuri D Phillips M Ravikumar B Padiyar AP 2011 Shocks recoverytrajectories and resilience among aquaculture-dependent households in post-tsunami
Aceh
Indonesia
Local
Environ
Int
J
Justice
Sustain
16
(5)
425ndash444Morduch J 1995 Income smoothing and consumption smoothing J Econ
Perspect 9 (3) 103ndash114Morris S Carletto C Hoddinott J Christiaensen L 2000 J Epidemiol Commun
Health 54 381ndash387Myers
RA
Worm
B
2003
Rapid
worldwide
depletion
of
predatory 1047297sh
communities Nature 423 280ndash283Nakagawa Y Shaw R 2004 Social capital a missing link to disaster recovery Int J
Mass
Emerg
Disasters
22
(1)
5ndash
34Nussbaum MC 2001 Adaptive preferences and womenrsquos options Econ Philos 1767ndash88
Oslashstergaard N Reenberg A 2010 Cultural barriers to climate change adaptation acase study from Northern Burkina Faso Glob Environ Change 20 (1) 142ndash152
OrsquoBrien K Leichenko R 2000 Double exposure assessing the impacts of climatechange within the context of economic globalization Glob Environ Change 10221ndash232
OrsquoBrien K Eriksen S Sygna L Naess LO 2006 Questioning complacencyclimate change impacts vulnerability and adaptation in Norway AMBIO JHum Environ 35 (2) 50ndash56
OrsquoBrien K Quilan T Ziervogel G 2009 Vulnerability interventions in the contextof multiple stressors lessons from the Southern Africa vulnerability initiative(SAVI) Environ Sci Policy 12 23ndash32
OrsquoRiordan T Jordan A 1999 Institutions climate change and cultural theorytowards a common analytical framework Glob Environ Change 9 (2) 81ndash93
Pain A Levine S 2012 A conceptual analysis of livelihoods and resilienceaddressing the
lsquoinsecurity of agency HPG Working Paper OverseasDevelopment Institute Humanitarian Policy Group London
Pauly D Christensen V Dalsgaard Froese JR Torres F 1998 Fishing downmarine food webs Science 279 (5352) 860ndash863
Pelling M Manuel-Navarrete D 2011 From resilience to transformation theadaptive cycle in two Mexican urban centersEcol Soc 16 (2)11 (online) httpwwwecologyandsocietyorgvol16iss2art11
Prowse
M
Scott
L
2008
Assets
and
adaptation
an
emerging
debate
IDS
Bull
39(4) 42ndash52
Putzel J 1997 Accounting for the lsquodark sidersquo of social capital reading Robert
Putnam
on
democracy
J
Int
Dev
9
(7)
939ndash949
Quinn CH Ziervogel G Taylor A Takama T Thomalla F 2011 Coping withmultiple
stresses
in
rural
South
Africa
Ecol
Soc
16
(3)
doihttpdxdoiorg105751ES-04216-160302
Reid P Vogel C 2006 Living and responding to multiple stressors in South Africamdashglimpses from KwaZulu-Natal Glob Environ Change 16 (2) 195ndash206
Roncoli C Ingram K Kirshen P 2001 The costs and risks of coping with droughtlivelihood
impacts
and
farmersrsquo
responses
in
Burkina
Faso
Clim
Res
19
119ndash132
Schwarz AM Beacuteneacute C Bennett G Boso D Hilly Z Paul C Posala R Sibiti SAndrew N 2011 Vulnerability and resilience of rural remote communities toshocks and global changes empirical analysis from the Solomon Islands GlobEnviron Change 21 1128ndash1140
Sinha
S
Lipton
M
Yaqub
S
2002
Poverty
and
damaging 1047298uctuations
how
dothey relate J Asian Afr Stud 37 (2) 186ndash243
Tansey J OrsquoRiordan T 1999 Cultural theory and risk a review Health Risk Soc 171ndash90
Teschl M Comim F 2005 Adaptive preferences and capabilities somepreliminary
conceptual
explorations
Rev
Soc
Econ
63
(2)
229ndash247
Trimble M Johnson D 2013 Artisanal 1047297shing as an undesirable way of life Theimplications for governance of 1047297shersrsquo wellbeing aspirations in coastal Uruguayand southeastern Brazil Mar Policy 37 37ndash44
Turner BL Kasperson RE Matson P McCarthy JJ Corell RW Christensen LEckley
N
Kasperson
JX
Luers
A
Martello
ML
Polsky
C
Pulsipher
ASchiller A 2003 A framework for vulnerability analysis in sustainabilityscience Proc Natl Acad Sci 100 (14) 8074ndash8079
Vigderhous G 1977 The level of measurement and
lsquoPermissiblersquo statistical analysisin social research Pac Sociol Rev 20 (1) 61ndash72
WFP 2013 Building Resilience Through Asset Creation Resilience and PreventionUnit
Policy
Programme
and
Innovation
Division
World
Food
Program
Rome(23 p)
Walker B Carpenter S Anderies J Abel N Cumming GS Janssen M Lebel LN J Peterson GD Pritchard R 2002 Resilience management in social-ecological systems a working hypothesis for a participatory approach ConservEcol
6
(1)
14Weber EU 2010 What shapes perceptions of climate change Clim Change 1 (3)
332ndash342
Wolf
J
Adger
WN
Lorenzoni
I
Abrahamson
V
Raine
R
2010
Social
capitalindividual responses to heat waves and climate change adaptation an empiricalstudy
of
two
UK
cities
Glob
Environ
Change
20
44ndash52Wood G 2003 Staying secure staying poor the Faustian bargain World Dev 31
(3) 455ndash471World Bank 2011 Building Resilience and Opportunities World Bankrsquos Social
Protection and Labour Strategy 2012ndash2022 World Bank Washington DCYamano T Alderman H Christiaensen L 2003 Child Growth Shocks and Food
Aid in Rural Ethiopia World Bank Washington DCZimmerman F Carter M 2003 Asset smoothing consumption smoothing and the
reproduction of inequality under risk and subsistence constraints J Dev Econ71 233ndash260
von Grebmer K Headey D Beacuteneacute C Haddad L et al 2013 Global Hunger IndexThe Challenge of Hunger Building Resilience to Achieve Food and NutritionSecurity Welthungerhilfe International Food Policy Research Institute andConcern Worldwide Bonn Washington DC and Dublin
170 C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
con1047297dence and the perception they had of their own ability to
restore their livelihood (Beacuteneacute et al 2015a) In these circumstances
it becomes as important to understand peoplersquos perceptions about
a particular event as it is to assess the actual objective impacts of
that particular event (Tansey and OrsquoRiordan 1999) The third key
hypothesis explored in this study was therefore that resilience is
subjectively constructed or at least is strongly in1047298uenced by social
and individual self-perception norms values and self-con1047297dence
in peoples ability to handle future events
3
Methods
and
data
31 Analytical framework
The last three to
1047297ve years have seen rapid progress in the
understanding of what (individual household community)
resilience is about supported by a growing body of primary and
grey literature see Frankenberger and Nelson (2013) for a recent
review Drawing on this literature we developed an analytical
framework to clarify the types of information needed to assess
peoplersquos resilience This framework which is shown on Fig 1
includes four main components (i) a shock and stressor inventory
and their impacts (ii) a household characteristics and wellbeing
assessment (iii) a householdsrsquo response typology and (iv) anoutcome analysis
Information was collected at both household and community
levels on the nature intensity and characteristics (frequency
duration date of occurrence) of the various shocks and stressors
experienced (idiosyncratic and co-variant events) The stochastic
characteristics of these events were expected to in1047298uence the type
of responses employed Accordingly a distinction was made
between three types of events (i) rapid shocks de1047297ned as short
and unpredictable adverse events affecting the lives andor
livelihoods of one or more members of the household (ii)
medium-term stressors de1047297ned as adverse events that last several
months andor occur recurrently and (iii) long-term trends that
occur graduallyincrementally and have potentially negative (or
positive) effect on peoples lives and livelihoodsThe household characteristics and wellbeing analysis covered
demographics and resource base (level of education age and
gender of the head size of the household etc) and socio-
economic status (economic wealth number and nature of income-
generating activities etc) Wealth was proxied by the level of
household assets as questionnaire-based assessment of household
income is notoriously unreliable and often provides an incomplete
picture of wealth (Morris et al 2000) In addition to these more
conventional variables data on ten domains of quality of life were
collected to capture and re1047298ect the multiple dimensions that are
considered to affect the wellbeing of households These ten
domains were collected because these dimensions and the level of
satisfaction that people experience in relation to them were
thought to be important factors in1047298uencing peoplersquos perception of
their ability to handle shocksstressors The analysis was therefore
expected to illuminate in greater detail what might be driving the
choice of the strategies that households make in an effort to
respond to shocksstressors The various types of responses to
shocks and stressors adopted by households were recorded and
coded into four main categories based on commonalities in
responses among households across the four countries (see
below)
Finally our framework was based on the premise that the
ultimate outcomes (general wellbeing food security or nutrition
status of a household) following an adverse event do not merely
result from the direct impact of that initial shock (eg destruction
of assets losses of livestock physical injuries) but instead are the
result of that shockrsquos impact combined with the responses
employed by individualshouseholds or communities to counter-act that shock as illustrated in Fig 1 To use a concrete example
when a household decides to send their eldest son to the capital
city following the loss of the latest harvest (or in our case say the
loss of 1047297shing gear) due to a strong tropical storm the ultimate
outcomes of this event is not merely the impact of the storm and
subsequent loss of 1047297shing gear but rather is the combination of
that impact with the consequences of the response put in place by
the household (sending the son away) A neighbour in the same
community who would have experienced the exact same event
(loss of 1047297shing gear due to the same tropical storm) might have
decided to respond differently (say by borrowing money) The
outcome for this second household will be different even though
exposed to the same initial shock
32 Data collection and statistical analyses
In the four focus countries Fiji (Paci1047297c) Vietnam and Sri Lanka
(Asia) and Ghana (Africa) small-scale
1047297sheries are known to be
an important basis for livelihoods in a large number of coastal
Fig 1 The analytical framework used for this resilience analysis made of four components (i) a shock and stressor inventory (ii) an household characteristics and wellbeing
assessment (iii) a response typology and (iv) an outcome analysis where the ultimate outcome is measured in terms of change in household wellbeing (eg food security or
nutrition for the justi1047297cation of this see Constas et al 2014b or Beacuteneacute et al 2015b) Note that as an analytical tool this framework is not intended to represent the full suite of
processes
and
feedback
loops
that
are
associated
with
learning
C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170 155
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
when all events are aggregated households are hit by a new event
of some kind every 485 days that is every 16 months
42 Household response analysis
The next step was to document and analyse the various types of
strategies that households employed in the face of shocks and
stressors In the resilience analysis framework (Fig 1) this
corresponds to the
lsquoresponse analysisrsquo component
Fig 4 presents the event-response matrices for the four country
case studies (computed for the ten most cited events per country)
The colour codes correspond to the four categories described in
Table 1 coping strategies social-relation based strategies 1047297shery-
related strategies and non-1047297shery-related strategies
The matrices show that coping strategies are the most frequent
responses put in place by households Amongst coping strategies
reduction of food consumption and reduction of general expenses
were commonly adopted while asset selling was notable for being
seldom adopted except in Ghana Beyond the generic pattern of
0 005 01 015 02 025 03 035
Others
High de
Destruconlossthe of fishing gear
Sudden change in sea condion
Slow increase in input prices
Major health problem
Death
Flood
Rapid (peak) increase in input prices
Decline in fish price
Sudden decli ne in catch
Slow decline in catch
Slow increase in food prices
Important change in fishing techniques
Any other fishery rela ted issue
unpredictable c hanges in weather
Hurricane
Percentage (total = 100)
Fiji
ST
MT
LT
0 005 01 015 02 025 03
Others
Increase in Food Price
Storm and strong winds
Unpred weather change
Accident Disability
Change in sea condion
Loss of financial assets
Loss of other assetsLoss fishing ground
Flood
Fish price increase
Sick family member
Death of family member
Destrucon The Loss gear
Input prices increase
Change in fishing techniques
Fuel shortage
Slow decline in catch
Percentage (total = 100)
Ghana
ST
MT
LT
0 005 01 015 0
Others
Slow but constant increase in input prices
Death of a family m ember
Other major weather event
Sudden change in sea condion
Flood
Sudden decline in catch
Loss of other assets other than fishing gear
Major health problem (sickness)
Decline in fish price
More unpredictable changes in weather paern
Important change in fishing techniquesSlow decline in catch
Limitaons-Harbour
New constraining fishing regulaon
Destruconlossthe of fishing gear
Rapid (peak) increase in input prices
Hurricane tropical storm
Perccentage (total = 100)
Sri Lanka
ST
MT
LT
0
005
01
015
02
025
03
035
04
045
Others
Lost assets
Accident
Erosion
Catch r educed suddently
Gears lost
Cold wind prolongs
Typhoon
Illness
Food price increase
Input price increa se connuously
Big boats compete ground and catch
Catch reduced connuously
Percentage (total = 100)
Vietnam
ST
MT
LT
Fig 2 Adverse event inventory for the four countries Events have been grouped and colour-coded into three categories short and unpredictable shocks (ST) (ii) medium-
term stressors that last several months andor are recurrent (MT) and (iii) long-term trends (LT)
0 10 20 30
Annually
On a connuous (daily) basis
Every 5 years
Bi-annually
Quarterly basis
Weekly basis
Monthly basis
Every two-year
Every 10 years
Every 20 year or less oen
Percentage of responses (total = 100)
(c) Event frequency
0
10
20
30
40
50
60
70
1 2 3 4 5
P e r c e n t a g e o f r e s p o n s e s ( t o t a l = 1 0 0 )
5-point scale rang
(b) Event severity
very bad lt ---------------------------------- gt posive
0
10
20
30
40
1 2 3 4 5
P e r c e n t a g e o f r e s p o n s e s ( t o t a l = 1 0 0 )
Fig 4 Event-response matrices for the four country case studies The numbers in the column are percentage of total responses ranked from the most (left) to the least (right)
adopted
and
colour-coded
using
the
typology
presented
in
Table
1 Full
details
are
provided
in
Appendix
A
Table 4
Average number of responses per event at the community level
Country Community Mean Std Err [95 Conf Interval]
Fiji A 27 022 232 317
B 26 007 244 272
Ghana C 43 018 389 461
D 39 016 359 421
Sri
Lanka
E
55
020
514
594F 76 026 707 809
Vietnam G 34 012 319 367
H 35 019 308 383
Total
(N
=
1868)
46
005
451
474
C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170 159
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
Resilience outcomes were explored using psychometric tech-
niques where households were asked to self-assess the degree of
recovery they managed to achieve for each of the adverse events
they had experienced in the past (see details in Table 2) The
answers provided by the respondents to the 1047297rst two questions of
the resilience analysis (self-recovery from past event and self-
recovery compared to the rest of the community) were used to
create a resilience index (RI) computed as the product of the two
scores As a result of the calculation process RI is an integer varying
between 1 and 30 where low values indicate low level of resilienceto a speci1047297c event while higher values indicate higher levels of
resilience
We then used this resilience index to explore the last remaining
working hypothesis of this research that is that
lsquosocial capital is
importantrsquo- ie the (intuitive) idea that households or communi-
ties characterized by higher level of social capital are able to draw
on social capital to help themselves (and others) in the aftermath
of an adverse event To analyse the resilience outcomes and explore
in particular this last hypothesis a three-level mixed effect linear
model was run where the resilience index was tested against a
series of 1047297xed and random factors used as independent explana-
tory variables Because the communities are nested within the
countries a three-level (hierarchical) model was
1047297tted with
random intercepts at both country and community-within-
country levels Random coef 1047297cients were also accounted for at
the country level on the Quality of Life (QoL) factors to re1047298ect
country speci1047297c effects More speci1047297cally the model was of the
form
RI vc frac14 b0 thorn b1Shockvc thorn b2Respvc thorn b3QoLvc thorn b4HH vc thorn g 1W c thorn g 2 Z vc thorn
evc
where the subscripts v and c hold for village (community) and
country respectively Shockvc is the covariate matrix for the
1047297xed
effect
b1 of the impacts of event e on individual household Respvc
is the covariate matrix for the 1047297xed effect b2 of the responses put in
places by the household QoLe is the covariate matrix for the
1047297xed
effect b3 of the Quality of Life scores recorded for each household
HH e is the matrix of variables and dummies controlling for
household characteristics W c is the covariate matrix for the cluster
random effect at the country level and Z vc is the covariate matrix
for the cluster random effect at the community level The details of
the different categories of variables included in the model are
provided in Table 6
Results of the model estimations including details of both
1047297xed and random effect speci1047297cations and diagnostic checking-
are presented in Table 7 The model highlights a series of important
1047297ndings First the degree of severity of the shock and the
disruptive impact on income are the twoshock variables that have
0
10
20
30
40
50
60
70
80
90
F o o d
E x p e n s e s
M o n e y
A s s e s t
S u p p o r t
C o l l a b o r a o n
D i v e r s i fi c a o n
M i g r a o n
E x i t
C h a n g e
I n c r e a s e
P e r c e n t a g e o f h o u s e h o l d s ( )
Response typology (Vietnam)
Boom 40
Top 40
0
01
02
03
04
05
06
07
F o o d
E x p e n s e s
M o n e y
A s s e t s
S u p p o r t
C o l l a b o r a o n
D i v e r s i fi c a o n
M i g r a o n
E x i t
C h a n g e
I n c r e a s e
P e r c e n t a g e o f h o u s e h o l d s ( )
Response typology (Fiji)Boom 40
Top 40
Fig 5 Comparative analysis of the responses adopted by the bottom (poorest) and top (wealthiest) 40 of the households when affected by the same event illustration
from Vietnam and Fiji Code of the responses
ldquoFoodrdquo = Reduce food consumption
ldquoExpensesrdquo = Reduce family general expenses
ldquoMoneyrdquo = Borrow money
ldquoAssetsrdquo = Sell
family assets
ldquoSupportrdquo= Seek for support from friends and peers
ldquoCollaborationrdquo= Develop new collaboration within the community
ldquoDiversi1047297cationrdquo = Invest in non-
1047297shery activities ldquoMigrationrdquo = Temporary permanently migration one or several members of the family ldquoExitrdquo = Exit the 1047297shery start a new joblivelihoodldquoChangerdquo = Change 1047297shing strategies
ldquoIncreaserdquo = Increase 1047297shing effort
160 C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
The type of responses adopted by households was included in
the model to test whether the level of resilience of households is
effectively in1047298uenced by those responses Amongst the 11 types of
responses tested three have statistically signi1047297cant signs engag-
ing
in
new
collaboration
(negative
sign
P
=
0001)
increasing1047297shing effort (positive P lt 00001) and quitting the
1047297shery
(negative P = 0047) The negative correlation found between
household resilience and the strategy that consists of forming new
collaboration may be dif 1047297cult to interpret as it can re1047298ect many
highly contextual factors The two others responses and the signs
of their correlations (one negative sign for leaving the sector and
one positive sign for increasing 1047297shing effort) are initially
disturbing but eventually not too surprising Disturbing
1047297rst
because this
1047297nding does not lead to the type of long-term
behaviours that appeal to policy makers and 1047297shery managers On
the contrary they would rather see 1047297shing effort reductions and
exit strategies more often adopted by
1047297shers in particular in the
context of the current world
1047297shery crisis Not surprising however
because this result is in line with what one could expect from
1047297sherfolks after an adverse event in the face of a long-term stress
(such
as
the
drop
in
income
following
a
continuous
decline
in
1047297shcatch) or a sudden need for cashrevenues (as a consequence of
eg destruction of 1047297shing gear induced by bad weather or the
need to pay health bills)
1047297shers are often observed to alter their
1047297shing activities to make up for these events usually by changing
adjusting their 1047297shing strategy (eg switching between targeted
species andor
1047297shing gear) or increasing their
1047297shing effort (eg
investing in more ef 1047297cient
1047297shing gear increasing the quantity of
gear used or increasing the number of days at sea) in an attempt to
generate more cash In that context it is not surprising that the
majority of 1047297shing households interviewed in this research
consider that their ability to
lsquobounce back following an adverse
event was enhanced when they increase their 1047297shing effort
Additionally given what we know about their strong sense of
identity
(Kelty
and
Kelty
2011
Trimble
and
Johnson
2013) but
alsothe importance of peer-pressure and reputation (see eg Beacuteneacute and
Tew1047297k 2001) quitting the 1047297shery would certainly be perceived by
many 1047297shers as a failure thus the negative correlation between
(perceived) resilience and leaving the sector
The next category of variables which was investigated through
the model was the Quality of Life indicators (see Table 3 for a
recall) A reasonable hypothesis although not explicitly formu-
lated in the
lsquoworking hypotheses section above- is that some of
these QoL indices may have a positive effect on the ability of
households to handle and recover from adverse events One can
indeed assume that households satis1047297ed in many of the
dimensions of wellbeing which they considers important (such
as say access to health services or to public infrastructure) may
feel better equipped to reactrespond to any particular event than
Table 5
Top comparison of propensities to adopt particular types of responses for households characterized by high (N = 224) and low (N = 235) subjective resilience Bottom
comparison of the two same groups in terms of asset levels education and age of the household head
Responses subjective
resilience
level
Mean [95 Conf
Interval]
test resulta
Coping strategies High 198 1840 2136 t = 43037 Pr(|T| gt |
t|) = 0000
Low 245 2311 2596
Social-relation-based strategies High 083 0738 0927 t = 05187 Pr(|T| gt |
t|) = 0604
Low 086 0787 0943
Fishing-related strategies High 083 0732 0935 t = 03267 Pr(|T| gt |
t|)
=
0744
Low 081 0715 0906
Non-1047297shery
strategies
High
067
0559
0794
t
=
35599
Pr(|T|
gt
|
t|) = 0000
Low 042 0341 0502
Household characteristics
Asset High 768 7218 8157 t = 08882 Pr(|T| gt |
t|) = 0374
Low 739 6938 7848
Education High 796 7338 8599 t = 10186 Pr(|T| gt |
t|)
=
0308
Low 750 6857 8147
Age High 4688 45377 48391 t = 01332 Pr(|T| gt |
t|) = 0894
Low 4702 45570 48482
p
lt 5
p
lt 1
p
lt 1
a mean difference unpaired t -test Ho Diff = 0 Ha diff 6frac14 0
C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170 161
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
diversif non 1047297sher diversi1047297cation dummy 1 = yes
exit_1047297sh exit the 1047297shery sector dummy 1 = yes
migrat migrate dummy 1 = yes
quality of life indices
index_incom
income
index
ordinal
variable
coded
[-6
+6]
ndash6
=
very
poor
+6
=
very
strong
index_livelih livelihood index ordinal variable coded [-6 +6] ndash6 = very poor +6 = very strongindex_housing housing and infrastructure index ordinal variable coded [-6 +6] ndash6 = very poor +6 = very strong
index_educ education index ordinal variable coded [-6 +6]
ndash6 = very poor +6 = very strong
index_soc social capital index ordinal variable coded [-6 +6]
ndash6 = very poor +6 = very strong
index_health health index ordinal variable coded [-6 +6] ndash6 = very poor +6 = very strong
ind_emp empowerment index ordinal variable coded [-6 +6]
ndash6 = very poor +6 = very strong
index_soc_cris social capital index in time of crisis
ndash6 = very poor +6 = very strong
index_emp_cris empowerment index in time of crisis
ndash6 = very poor +6 = very strong
index_spirit index of spirituality
ordinal variable coded [-6 +6]
ndash6 = very poor +6 = very strong
household characteristics
HH head sex sex of household head dummy 1 = female
HH
head
age
age
of
household
head
age
in
years
HH head educ level of education of the household head 0 = no education 20 = post-graduate level
HH size size of household number of members (not adjusted for age)
log_asset household assets (log-transformed) value of household assets (proxy for wealth level)
community
resiliencecomm_recov level of recovery of the community
a Fitting a three level model requires two random-effect equations one for level three (country) and one for level two (community) with i = 1 nvc 1047297rst level of
observation (households) nested within k = 1 8 s level cluster (community) nested within j = 1 4 third level cluster (country)
162 C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
community level in the same way than the QoL indices that is by
averaging the scores obtained at the individual household level)
The best correlation was obtained with the QoL index of social
capital in time of crisis (R 2= 077 F = 0004) see Fig 6- suggesting
that communities with higher social capital in time of crisis are
also characterized by higher level of resilience
5 Discussion
Resilience has been increasingly recognized as a potentially
useful concept to help practitioners academics and policy-makers
better understand the links between shocks response and longer-
term development outcomes (Constas et al 2014a Beacuteneacute et al
2014) Incorporating resilience alongside vulnerability analysis can
contribute an essential element to societal ability to better prepare
for future shocks and stressors This paper argues that improving
our understanding of what contributes to or constitutes peoplersquos
resilience requires not only the development and
1047297eld-testing of
robust and measurable indices (Beacuteneacute 2013 Constas et al 2014b)
but also a better insight into the social factors including
knowledge perceptions and motivations- that in1047298uence and affect
individual and collective capacity to respond to shocks and
stressors
Our analysis conducted in eight 1047297shery-dependent communi-
ties from Fiji Ghana Sri Lanka and Vietnam reveals a series of
notable results in relation to these questions In considering these
outcomes it is important to 1047297rst take stock of potential limitations
pitfalls or biases in the study methodology Given the nature of the
1047297ndings two potential issues require further consideration First is
the question of how representative our sampling methodology
was It could be argued for instance that the observed low adoption
rates of non-1047297shery strategiesndash and in particular the low score of
the
lsquoexiting the
1047297sheryrsquo was driven by our sampling method
underrepresenting these groups as those who had effectively left
the 1047297shery were not included in the sample
The FGDs that preceded the household survey speci1047297cally
addressed this issue In Sri Lanka for instance the opening question
prompted participants (both men and women) to discuss whether
ldquo1047297shers in their community had ever left 1047297sheries due to their
inability to cope with adverse eventsrdquo The answer was that it
generally does not happen with the notable exception of someyoung
1047297shers who attempted to migrate to Australia through
illegal means If it occurred exiting the 1047297shery was said to be
temporary ldquothey may leave the village or 1047297shing but will come
back when the situation is favourablerdquo In Vietnam the sampling
was speci1047297cally designed to cover both
1047297shers and ex-1047297shers in
proportions represented in the community As a result 9 ex-1047297shers
were included in the sample Overall therefore although we were
unable to conceive of a completely representative sampling design
(in the statistical sense) the parallel information that was collected
in the FGDs and the individual households converge to suggest that
exiting the
1047297shery was not an option envisaged by the members of
these different communities and consequently that our sampling
was not too severely biased
0
2
4
6
8
10
12
14
16
-05 05 15 25
C o m m u n i t y l e v e l r e s i l i
e n c e i n d e x
Community level social capital in me of crisis
Fiji
Ghana
Sri Lanka
Vietnam
Fig 6 Correlation between social capital in time of crisis and resilience index
across the eight communities The straight line represents the linear relation
(R 2 = 077 F = 0004) and the bars are 95 con1047297dence intervals for each community
Random-effects parameters St Dev Std Err [95 Conf Interval]
country level
index_incom 043 024 0146 1266
index_livelih 051 027 0175 1464
index_housing 013 013 0018 0962
index_soc 039 024 0119 1303
index_soc_cris
078
038
0300
2009index_educ 015 013 0028 0834
const 090 067 0209 3861
community level
const 032 026 0066 1534
residuals 277 008 2617 2923
LR test vs linear regression chi2(7) = 3916 Prob gt chi2= 0000
p
lt 5
p
lt
1 p lt 1ma Fitting a three level model requires two random-effect equations one for level three (country) and one for level two (community) with i = 1 nvc 1047297rst level of
observation
(households)
nested
within
k
=
1
8
second
level
cluster
(community)
nested
within
j
=
1
4
third
level
cluster
(country)b The likelihood-ratio (LR) test comparing the nested mixed-effects model with the corresponding 1047297xed effect model con1047297rms the appropriate use of the mixed effect
model (chi2(7) = 3916 Prob gt chi2= 0000) and the Wald test con1047297rms that the independent variables are valid predictors (Wald chi2(45) = 59414 Prob gt chi2= 0000) A
speci1047297cation test performed on the 1047297xed effect model using a Pregibonrsquos goodness-of-link test shows good results (t = 077 P gt |t| = 0439)
c The dummy variables sev_event3 cat_event2 predict2 and comm_recov3 were omitted from the 1047297xed effect component for estimation purpose
Table 7 (Continued)
164 C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
The second potential limitation in our methodology relates to
the way the level of resilience of the households was assessed
While psychometric measurements are reliable and their results
replicable and testable when correctly implemented (Vigderhous
1977) one could fear that their use in the speci1047297c case of resilience
measurement could be subject to the effect of adaptive preference
that is the deliberate or re1047298exive process by which people adjust
their expectations and aspirations when trying to cope with
deterioration in living conditions (see eg Nussbaum 2001 Teschl
and Comim 2005) In our case this means that households
undergoing a degree of adaptive preference could have over-
estimated their ability to recover Although this risk is present we
tried to mitigate (or to reduce) it by introducing a qualifying
element in each of the coded answers of the resilience question-
naire so that respondents would have to associate the
1047297rst part of
their answer ldquoI have fully recoveredrdquo with a particular lsquoframe of
reference or quali1047297er (eg ldquoand it was not too dif 1047297cultrdquo) This frame
determined how they comprehend the questions being asked and
reduced the risk of the respondent simply relying on emotional
elements to answer these questions
Keeping in mind these potential limitations we now turn to
what we consider the most notable results of this research First is
the
lsquocumulative and continuous effect of shocks and stressors
whereby the impacts and disturbance of sequential shocksstressors and trends during the last 1047297ve years combine and
coalesce to create a constant non-stop stress We saw that the
nature and the source of events that were identi1047297ed by the
respondents in the four countries are all highly varied and
composite and reveal no speci1047297c clear pattern The events are a
combination of idiosyncratic and covariant sudden shocks and
long-term continuous trends Some are predictable while others
are totally unexpected All affect households simultaneously and
on an almost continuous basis The data suggests in particular that
on average households are hit by a new event every 16 months
This result calls into questions the framework generally used to
conduct shock or vulnerability assessment Often the approach has
been to disaggregate the problems people face and focus on single
threats such as eg 1047298ood or increase in food prices in order todevelop a clearer understanding of the impact of these particular
shocks and the ways people respond to them This approach has
been challenged however by a growing number of scholars who
argue that the reality households face on a daily basis is not linear
and mono-dimensional (OrsquoBrien and Leichenko 2000 Eriksen and
Silva 2009 Quinn et al 2011 McGregor 2011) Instead they argue
risks and vulnerability are often the product of multiple stressors
(Turner et al 2003 OrsquoBrien et al 2009) where social economic
political and biophysical factors interact combine and reinforce
each other to create a complex and dynamic multi-stressor multi-
shock environment (Reid and Vogel 2006 Adger 2006) Our
results corroborate this new interpretation
In line with this our analysis also shows that most households
engage in a suite of responses to a given shock On average
households adopted more than 4 types of responses to a particular
event This last result does not simply imply a rethinking of the way
shock or vulnerability assessments are conceptualized and
conducted see eg Turner et al (2003) or Leichenko and OrsquoBrien
(2008) It also demonstrates that the mental model (shock
gt response gt recovery) which is widely accepted in the
resilience literature is too simplistic and possibly misleading in
the sense that a state of (full) recovery may not exist This is at least
what was observed for the households included in our research
these households did not seem to have the chance or the time to
fully recover from one particular event before being affected by the
next Instead they were caught in what we could characterize as ldquoaconstant state of incomplete recoveringrdquo from new shocks and
stressors as illustrated in Fig 7
The next entry point in this discussion is wealth Our mixed
effect model (Table 7) shows that wealth was positively correlated
with household resilience Wealth has been identi1047297ed in the
literature as a key factor in strengthening the resilience of
households (Prowse and Scott 2008 WFP 2013) Analysis of
rural Ethiopian households hit by drought for instance showed that
while better-off households could sell livestock to smooth
consumption the poorer often tried to hold on to their livestock
at the expense of food consumption to preserve their options for
rebuilding herds The same study also shows that in the aftermath
of the hurricane Mitch in Honduras the relatively wealthy
households were able to rebuild their lost assets faster than thepoorest households for whom the effects of the hurricane were of
longer duration and felt much more acutely (Carter et al 2007) In
Fig 7 Left Current conceptualisation of resilience shock gt response gt recovery as presented in the literature [here redrawn from Carter et al 2007] Right actual
situation where the multi-stressor multi-shock environment induces that households are in a trajectory of continual and incomplete recovery Not represented here are the
multi-response
strategies
put
in
place
by
households
to
respond
to
these
adverse
events
C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170 165
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
disaster resilience National Disaster Resilience Roundtable Report 20September 2012 Melbourne Australia 36 p
Adger NW Dessai S Goulden M Hulme M Lorenzoni I Nelson DR Naess LO Wolf J Wreford A 2009 Are there social limits to adaptation to climatechange
Clim
Change
93
335ndash354Adger WN 2003 Social capital collective action and adaptation to climate
change Econ Geogr 79 (4) 387ndash404Adger WN 2006 Vulnerability Glob Environ Change 16 268ndash281Aldrich D 2010 Fixing recovery social capital in post-Crisis resilience J Homeland
Secur 6 1ndash10Ayers
J
Forsyth
T
2009
Community-based
adaptation
to
climate
changestrengthening resilience through development Environment 51 23ndash31
Beacuteneacute C Tew1047297k A 2001 Fishing effort allocation and 1047297shermenrsquos decision-makingprocess in a multi-species small-scale 1047297shery analysis of the conch and lobster1047297shery in Turks and Caicos Islands Hum Ecol 29 (2) 157ndash186
Beacuteneacute
C
Evans
L
Mills
D
Ovie
S
Raji
A
Ta1047297da
A
Kodio
A
Sinaba
F
Morand
PLemoalle J Andrew N 2011 Testing resilience thinking in a poverty contextexperience from the Niger river basin Glob Environ Change 21 (4) 1173ndash1184
Beacuteneacute C Godfrey-Wood R Newsham A Davies M2012 Resilience new utopia ornew tyranny
ndash Re1047298ection about the potentials and limits of the concept of
resilience
in
relation
to
vulnerability
reduction
programmes
IDS
Working
Paperno 405 Institute of Development Studies Brighton 61 p
Beacuteneacute C Newsham A Davies M Ulrichs M Godfrey-Wood R 2014 Resiliencepoverty and development J Int Dev 26 598ndash623
Beacuteneacute C Waid J Jackson-deGraffenried M Begum A Chowdhury M Skarin VRahman A Islam N Mamnun N Mainuddin K Shah MA 2015a Impact of climate-related
shocks
and
stresses
on
nutrition
and
food
security
in
ruralBangladesh Dhaka World Food Programme 119 p
Beacuteneacute C Frankenberger T Nelson S 2015b Design monitoring and evaluation of resilience interventions conceptual and empirical considerations IDS WorkingPaper no459 Institute of Development Studies 23 p
Beacuteneacute
C
2013
Towards
a
quanti1047297able
measure
of
resilience
IDS
Working
Paper
434Institute of Development Studies Brighton 27 p
Bandura A 1977 Self-ef 1047297cacy toward a unifying theory of behavioral changePsychol Rev 84 191ndash215
Baulch R Hoddinott J 2000 Economic mobility and poverty dynamics indeveloping countries J Dev Stud 36 (6) 1ndash23
Belhabib
D
Sumaila
UR
Pauly
D
2015
Feeding
the
poor
contribution
of
WestAfrican 1047297sheries to employment and food security Ocean Coast Manage 11172ndash81
Berkes F Folke C 1998 Linking social and ecological systems for resilience andsustainability In Berkes F Folke C (Eds) Linking Social and EcologicalSystems Management Practices and Social Mechanisms for Building ResilienceCambridge University Press Cambridge pp 1ndash25
Bernier Q Meinzen-Dick R 2014 Resilience and social capital Building Resiliencefor Food and Nutrition Security Conference Paper No 4 International FoodPolicy Research Institute Washington DC 26 p
Bhattamishra R Barrett C 2010 Community-Based risk managementarrangements a review World Dev 38 (7) 923ndash932
Boarini R Kolev A McGregor JA 2014 Measuring well-being and progress incountries at different stages of development towards a more universalconceptual framework OECD Working Paper No 235 Organisation forEconomic Co-operation and Development Development Center
ndash Better Life
Initiative Paris 59 p
Boyd E Osbahr H Ericksen P Tompkins E Carmen Lemos M Miller F 2008Resilience and
lsquoclimatizingrsquo development examples and policy implicationsDevelopment 51 390ndash396
Cam1047297eld
L
McGregor
JA
2005
Resilience
and
wellbeing
in
developing
countriesIn Ungar M (Ed) Handbook for Working with Children and Youth Pathwaysto Resilience Across Cultures and Contexts Sage Publications Thousand OaksCA
Cam1047297eld
L
Ruta
D
2007
Translation
is
not
enough
using
the
Global
PersonGenerated Index (GPGI) to assess individual quality of life in BangladeshThailand and Ethiopia Qual Life 16 (6) 1039ndash1051
Carter M Little P Mogues T Negatu W 2007 Poverty traps and natural disastersin Ethiopia and Honduras World Dev 35 (5) 835ndash856
Cleaver
F
2005
The
inequality
of
social
capital
and
the
reproduction
of
chronicpoverty World Dev 33 (6) 893ndash906
Constas M Frankenberger T Hoddinott J 2014a Resilience measurementprinciples toward an agenda for measurement design Resilience MeasurementTechnical Working Group Technical Series No 1 Food Security informationNetwork Rome
Constas MT Frankenberger J Hoddinott N Mock D Romano C Beacuteneacute DMaxwell 2014b A common analytical model for resilience measurementcausal framework and methodological options Food Security InformationNetwork (FSIN) Technical Series No 2 World Food Programme Rome
Coulthard S 2011 More than just access to 1047297sh the pros and cons of 1047297sherparticipation
in
a
customary
marine
tenure
(Padu)
system
under
pressure
MarPolicy 35 405ndash412
DFID 2011 De1047297ning Disaster Resilience A DFID Approach Paper Department forInternational Development London pp 20
Dercon S Hoddinott J Woldehanna T 2005 Shocks and consumption in 15ethiopian
villages
1999ndash2004
J
Afr
Econ
14
(4)
559ndash585Dercon S 1996 Risk crop choice and savings evidence from Tanzania Econ Dev
Cult Change 44 (3) 485ndash513Duit A Galaz V Eckerberg K 2010 Governance complexity and resilience Glob
Environ Change 20 (3) 363ndash368Eriksen
SEH
Silva
JA
2009
The
vulnerability
context
of
a
savannah
area
inMozambique household drought coping strategies and responses to economicchange Environ Sci Policy 12 (1) 33ndash52
Fafchamps M Lund S 2003 Risk-Sharing networks in rural Philippines J DevEcon 71 (2) 261ndash287
Frankenberger T Nelson S 2013 Background Paper for the Expert Consultation onResilience
Measurement
for
Food
Security
TANGO
International
Rome
Foodand Agricultural Organization and World Food Program
Heltberg R Siegel PS Jorgensen SL 2009 Addressing human vulnerability toclimate change towards a
lsquono-regretsrsquo approach Glob Environ Change 19 89ndash99
Hoddinott
J
Dercon
S
Krishnan
P
2009
Networks
and
informal
mutual
supportin 15 ethiopian villages a description In Kirsten JF Dorward AR Poulton CVink N (Eds) Institutional Economics Perspectives on African AgriculturalDevelopment International Food Policy Research Institute Washington DC pp273ndash286
Hoddinott
J
2006
Shocks
and
their
consequences
across
and
within
households
inRural Zimbabwe J Dev Stud 42 (2) 301ndash321
Intergovernmental Panel on Climate Change (IPCC) 2012 In Field CB Barros VStocker TF Qin D Dokken DJ Ebi KL Mastrandrea MD Mach KJPlattner G-K Allen SK Tignor MMidgley PM (Eds) Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation A SpecialReport of Working Groups I and II of the Intergovernmental Panel on ClimateChange Cambridge University Press Cambridge UK
Jackson T 2005 Motivating sustainable consumptionmdasha review of evidence onconsumer behaviour and behavioural change A Report to the Sustainable
Event type (Vietnam) Reduce
expenditures
Borrow
money
Reduce
Food
Change
1047297shing
strategy
Get
support
Increase
1047297shing
effort
Diversi1047297cation Seek new
collaboration
Migration Exit the
1047297shery
Sell
assets
Total
Others (aggregated) 4 7 4 6 3 0 1 3 0 0 2 30
Erosion 2 4 2 1 6 2 2 2 3 1 25
Catch reduced
suddenly
8 4 6 7 1 2 4 2 34
Gears lost 10 18 6 5 1 2 1 43
Cold wind prolongs 15 7 11 3 1 7 2 46
Typhoon
12
11
10
2
4
2
3
5
4
1
1
55
Illness
11 14
6
2
11
2
2
4
1
1
2
56Food price increase 20 17 19 2 8 5 1 72
Input price increase
continuously
47 39 33 21 40 5 6 16 1 208
Big boats compete
ground and catch
54 39 32 40 9 19 11 15 8 3 2 232
Catch
reduced
continuously
102
70
80
63
22
51
51
25
23
17
6
510
Total 285 230 209 152 105 91 87 75 39 23 15 1311
C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170 169
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
Development Research Network Centre for Environmental StrategiesUniversity of Surrey
Jones L Boyd E 2011 Exploring social barriers to adaptation insights fromWestern Nepal Glob Environ Change 21 (4) 1262ndash1274
Kallstrom HN Ljung M 2005 Social sustainability and collaborative learningAmbio 34 376ndash382
Kelty R Kelty R 2011 Human dimensions of a 1047297shery at a crossroads resourcevaluation identity and way of life in a seasonal 1047297shing community Soc NatResour
24
(4)
334ndash348Klein RJT Nicholls RJ Thomalla F 2003 Resilience to natural hazards how
useful is this concept Environ Hazards 5 35ndash45
Krosnick
JA
Fabrigar
LR
1997
Designing
rating
scales
for
effective
measurementin surveys In Lyberg L Biemer P Collins M de Leeuw E Dippo C SchwarzN
Trewin
D
(Eds)
Survey
Measurement
and
Process
Quality
John
Wiley
andSons Inc New York NY pp 141ndash164
Leichenko R OrsquoBrien K 2008 Environmental Change and Globalization DoubleExposures Oxford University Press New York
Marschke M Berkes F 2006 Exploring Strategies that build livelihood resiliencea case from Cambodia Ecol Soc 11 (1) httpwwwecologyandsocietyorgvol11iss1art42
McGregor JA Cam1047297eld L Woodcock A 2009 Needs wants and goals wellbeingquality
of
life
and
public
policy
Appl
Res
Qual
Life
4
135ndash154McGregor JA 1994 Village credit and the reproduction of poverty in rural
Bangladesh In Acheson J (Ed) Economic Anthropology and the NewInstitutional Economics University Press of AmericaSociety for EconomicAnthropology Washington pp 261ndash281 (Chapter)
McGregor
JA
2011
Reimagining
development
through
the
crisis
watch
initiative
IDS Bull 42 (5) 17ndash23McLaughlin P Dietz T 2007 Structureagency and environment toward an
integrated perspective on vulnerability Glob Environ Change 39 (4) 99ndash111Meyer MA 2013 Social capital and resilience in the context of disaster social
capital
and
collective
ef 1047297cacy
for
disaster
resilience
connecting
individualswith communities and vulnerability with resilience in hurricane-pronecommunities in Florida PhD Dissertation Department of sociology Coloradostate University Fort Collins Colorado (311 p)
Mills DJ Adhuri D Phillips M Ravikumar B Padiyar AP 2011 Shocks recoverytrajectories and resilience among aquaculture-dependent households in post-tsunami
Aceh
Indonesia
Local
Environ
Int
J
Justice
Sustain
16
(5)
425ndash444Morduch J 1995 Income smoothing and consumption smoothing J Econ
Perspect 9 (3) 103ndash114Morris S Carletto C Hoddinott J Christiaensen L 2000 J Epidemiol Commun
Health 54 381ndash387Myers
RA
Worm
B
2003
Rapid
worldwide
depletion
of
predatory 1047297sh
communities Nature 423 280ndash283Nakagawa Y Shaw R 2004 Social capital a missing link to disaster recovery Int J
Mass
Emerg
Disasters
22
(1)
5ndash
34Nussbaum MC 2001 Adaptive preferences and womenrsquos options Econ Philos 1767ndash88
Oslashstergaard N Reenberg A 2010 Cultural barriers to climate change adaptation acase study from Northern Burkina Faso Glob Environ Change 20 (1) 142ndash152
OrsquoBrien K Leichenko R 2000 Double exposure assessing the impacts of climatechange within the context of economic globalization Glob Environ Change 10221ndash232
OrsquoBrien K Eriksen S Sygna L Naess LO 2006 Questioning complacencyclimate change impacts vulnerability and adaptation in Norway AMBIO JHum Environ 35 (2) 50ndash56
OrsquoBrien K Quilan T Ziervogel G 2009 Vulnerability interventions in the contextof multiple stressors lessons from the Southern Africa vulnerability initiative(SAVI) Environ Sci Policy 12 23ndash32
OrsquoRiordan T Jordan A 1999 Institutions climate change and cultural theorytowards a common analytical framework Glob Environ Change 9 (2) 81ndash93
Pain A Levine S 2012 A conceptual analysis of livelihoods and resilienceaddressing the
lsquoinsecurity of agency HPG Working Paper OverseasDevelopment Institute Humanitarian Policy Group London
Pauly D Christensen V Dalsgaard Froese JR Torres F 1998 Fishing downmarine food webs Science 279 (5352) 860ndash863
Pelling M Manuel-Navarrete D 2011 From resilience to transformation theadaptive cycle in two Mexican urban centersEcol Soc 16 (2)11 (online) httpwwwecologyandsocietyorgvol16iss2art11
Prowse
M
Scott
L
2008
Assets
and
adaptation
an
emerging
debate
IDS
Bull
39(4) 42ndash52
Putzel J 1997 Accounting for the lsquodark sidersquo of social capital reading Robert
Putnam
on
democracy
J
Int
Dev
9
(7)
939ndash949
Quinn CH Ziervogel G Taylor A Takama T Thomalla F 2011 Coping withmultiple
stresses
in
rural
South
Africa
Ecol
Soc
16
(3)
doihttpdxdoiorg105751ES-04216-160302
Reid P Vogel C 2006 Living and responding to multiple stressors in South Africamdashglimpses from KwaZulu-Natal Glob Environ Change 16 (2) 195ndash206
Roncoli C Ingram K Kirshen P 2001 The costs and risks of coping with droughtlivelihood
impacts
and
farmersrsquo
responses
in
Burkina
Faso
Clim
Res
19
119ndash132
Schwarz AM Beacuteneacute C Bennett G Boso D Hilly Z Paul C Posala R Sibiti SAndrew N 2011 Vulnerability and resilience of rural remote communities toshocks and global changes empirical analysis from the Solomon Islands GlobEnviron Change 21 1128ndash1140
Sinha
S
Lipton
M
Yaqub
S
2002
Poverty
and
damaging 1047298uctuations
how
dothey relate J Asian Afr Stud 37 (2) 186ndash243
Tansey J OrsquoRiordan T 1999 Cultural theory and risk a review Health Risk Soc 171ndash90
Teschl M Comim F 2005 Adaptive preferences and capabilities somepreliminary
conceptual
explorations
Rev
Soc
Econ
63
(2)
229ndash247
Trimble M Johnson D 2013 Artisanal 1047297shing as an undesirable way of life Theimplications for governance of 1047297shersrsquo wellbeing aspirations in coastal Uruguayand southeastern Brazil Mar Policy 37 37ndash44
Turner BL Kasperson RE Matson P McCarthy JJ Corell RW Christensen LEckley
N
Kasperson
JX
Luers
A
Martello
ML
Polsky
C
Pulsipher
ASchiller A 2003 A framework for vulnerability analysis in sustainabilityscience Proc Natl Acad Sci 100 (14) 8074ndash8079
Vigderhous G 1977 The level of measurement and
lsquoPermissiblersquo statistical analysisin social research Pac Sociol Rev 20 (1) 61ndash72
WFP 2013 Building Resilience Through Asset Creation Resilience and PreventionUnit
Policy
Programme
and
Innovation
Division
World
Food
Program
Rome(23 p)
Walker B Carpenter S Anderies J Abel N Cumming GS Janssen M Lebel LN J Peterson GD Pritchard R 2002 Resilience management in social-ecological systems a working hypothesis for a participatory approach ConservEcol
6
(1)
14Weber EU 2010 What shapes perceptions of climate change Clim Change 1 (3)
332ndash342
Wolf
J
Adger
WN
Lorenzoni
I
Abrahamson
V
Raine
R
2010
Social
capitalindividual responses to heat waves and climate change adaptation an empiricalstudy
of
two
UK
cities
Glob
Environ
Change
20
44ndash52Wood G 2003 Staying secure staying poor the Faustian bargain World Dev 31
(3) 455ndash471World Bank 2011 Building Resilience and Opportunities World Bankrsquos Social
Protection and Labour Strategy 2012ndash2022 World Bank Washington DCYamano T Alderman H Christiaensen L 2003 Child Growth Shocks and Food
Aid in Rural Ethiopia World Bank Washington DCZimmerman F Carter M 2003 Asset smoothing consumption smoothing and the
reproduction of inequality under risk and subsistence constraints J Dev Econ71 233ndash260
von Grebmer K Headey D Beacuteneacute C Haddad L et al 2013 Global Hunger IndexThe Challenge of Hunger Building Resilience to Achieve Food and NutritionSecurity Welthungerhilfe International Food Policy Research Institute andConcern Worldwide Bonn Washington DC and Dublin
170 C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
con1047297dence and the perception they had of their own ability to
restore their livelihood (Beacuteneacute et al 2015a) In these circumstances
it becomes as important to understand peoplersquos perceptions about
a particular event as it is to assess the actual objective impacts of
that particular event (Tansey and OrsquoRiordan 1999) The third key
hypothesis explored in this study was therefore that resilience is
subjectively constructed or at least is strongly in1047298uenced by social
and individual self-perception norms values and self-con1047297dence
in peoples ability to handle future events
3
Methods
and
data
31 Analytical framework
The last three to
1047297ve years have seen rapid progress in the
understanding of what (individual household community)
resilience is about supported by a growing body of primary and
grey literature see Frankenberger and Nelson (2013) for a recent
review Drawing on this literature we developed an analytical
framework to clarify the types of information needed to assess
peoplersquos resilience This framework which is shown on Fig 1
includes four main components (i) a shock and stressor inventory
and their impacts (ii) a household characteristics and wellbeing
assessment (iii) a householdsrsquo response typology and (iv) anoutcome analysis
Information was collected at both household and community
levels on the nature intensity and characteristics (frequency
duration date of occurrence) of the various shocks and stressors
experienced (idiosyncratic and co-variant events) The stochastic
characteristics of these events were expected to in1047298uence the type
of responses employed Accordingly a distinction was made
between three types of events (i) rapid shocks de1047297ned as short
and unpredictable adverse events affecting the lives andor
livelihoods of one or more members of the household (ii)
medium-term stressors de1047297ned as adverse events that last several
months andor occur recurrently and (iii) long-term trends that
occur graduallyincrementally and have potentially negative (or
positive) effect on peoples lives and livelihoodsThe household characteristics and wellbeing analysis covered
demographics and resource base (level of education age and
gender of the head size of the household etc) and socio-
economic status (economic wealth number and nature of income-
generating activities etc) Wealth was proxied by the level of
household assets as questionnaire-based assessment of household
income is notoriously unreliable and often provides an incomplete
picture of wealth (Morris et al 2000) In addition to these more
conventional variables data on ten domains of quality of life were
collected to capture and re1047298ect the multiple dimensions that are
considered to affect the wellbeing of households These ten
domains were collected because these dimensions and the level of
satisfaction that people experience in relation to them were
thought to be important factors in1047298uencing peoplersquos perception of
their ability to handle shocksstressors The analysis was therefore
expected to illuminate in greater detail what might be driving the
choice of the strategies that households make in an effort to
respond to shocksstressors The various types of responses to
shocks and stressors adopted by households were recorded and
coded into four main categories based on commonalities in
responses among households across the four countries (see
below)
Finally our framework was based on the premise that the
ultimate outcomes (general wellbeing food security or nutrition
status of a household) following an adverse event do not merely
result from the direct impact of that initial shock (eg destruction
of assets losses of livestock physical injuries) but instead are the
result of that shockrsquos impact combined with the responses
employed by individualshouseholds or communities to counter-act that shock as illustrated in Fig 1 To use a concrete example
when a household decides to send their eldest son to the capital
city following the loss of the latest harvest (or in our case say the
loss of 1047297shing gear) due to a strong tropical storm the ultimate
outcomes of this event is not merely the impact of the storm and
subsequent loss of 1047297shing gear but rather is the combination of
that impact with the consequences of the response put in place by
the household (sending the son away) A neighbour in the same
community who would have experienced the exact same event
(loss of 1047297shing gear due to the same tropical storm) might have
decided to respond differently (say by borrowing money) The
outcome for this second household will be different even though
exposed to the same initial shock
32 Data collection and statistical analyses
In the four focus countries Fiji (Paci1047297c) Vietnam and Sri Lanka
(Asia) and Ghana (Africa) small-scale
1047297sheries are known to be
an important basis for livelihoods in a large number of coastal
Fig 1 The analytical framework used for this resilience analysis made of four components (i) a shock and stressor inventory (ii) an household characteristics and wellbeing
assessment (iii) a response typology and (iv) an outcome analysis where the ultimate outcome is measured in terms of change in household wellbeing (eg food security or
nutrition for the justi1047297cation of this see Constas et al 2014b or Beacuteneacute et al 2015b) Note that as an analytical tool this framework is not intended to represent the full suite of
processes
and
feedback
loops
that
are
associated
with
learning
C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170 155
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
when all events are aggregated households are hit by a new event
of some kind every 485 days that is every 16 months
42 Household response analysis
The next step was to document and analyse the various types of
strategies that households employed in the face of shocks and
stressors In the resilience analysis framework (Fig 1) this
corresponds to the
lsquoresponse analysisrsquo component
Fig 4 presents the event-response matrices for the four country
case studies (computed for the ten most cited events per country)
The colour codes correspond to the four categories described in
Table 1 coping strategies social-relation based strategies 1047297shery-
related strategies and non-1047297shery-related strategies
The matrices show that coping strategies are the most frequent
responses put in place by households Amongst coping strategies
reduction of food consumption and reduction of general expenses
were commonly adopted while asset selling was notable for being
seldom adopted except in Ghana Beyond the generic pattern of
0 005 01 015 02 025 03 035
Others
High de
Destruconlossthe of fishing gear
Sudden change in sea condion
Slow increase in input prices
Major health problem
Death
Flood
Rapid (peak) increase in input prices
Decline in fish price
Sudden decli ne in catch
Slow decline in catch
Slow increase in food prices
Important change in fishing techniques
Any other fishery rela ted issue
unpredictable c hanges in weather
Hurricane
Percentage (total = 100)
Fiji
ST
MT
LT
0 005 01 015 02 025 03
Others
Increase in Food Price
Storm and strong winds
Unpred weather change
Accident Disability
Change in sea condion
Loss of financial assets
Loss of other assetsLoss fishing ground
Flood
Fish price increase
Sick family member
Death of family member
Destrucon The Loss gear
Input prices increase
Change in fishing techniques
Fuel shortage
Slow decline in catch
Percentage (total = 100)
Ghana
ST
MT
LT
0 005 01 015 0
Others
Slow but constant increase in input prices
Death of a family m ember
Other major weather event
Sudden change in sea condion
Flood
Sudden decline in catch
Loss of other assets other than fishing gear
Major health problem (sickness)
Decline in fish price
More unpredictable changes in weather paern
Important change in fishing techniquesSlow decline in catch
Limitaons-Harbour
New constraining fishing regulaon
Destruconlossthe of fishing gear
Rapid (peak) increase in input prices
Hurricane tropical storm
Perccentage (total = 100)
Sri Lanka
ST
MT
LT
0
005
01
015
02
025
03
035
04
045
Others
Lost assets
Accident
Erosion
Catch r educed suddently
Gears lost
Cold wind prolongs
Typhoon
Illness
Food price increase
Input price increa se connuously
Big boats compete ground and catch
Catch reduced connuously
Percentage (total = 100)
Vietnam
ST
MT
LT
Fig 2 Adverse event inventory for the four countries Events have been grouped and colour-coded into three categories short and unpredictable shocks (ST) (ii) medium-
term stressors that last several months andor are recurrent (MT) and (iii) long-term trends (LT)
0 10 20 30
Annually
On a connuous (daily) basis
Every 5 years
Bi-annually
Quarterly basis
Weekly basis
Monthly basis
Every two-year
Every 10 years
Every 20 year or less oen
Percentage of responses (total = 100)
(c) Event frequency
0
10
20
30
40
50
60
70
1 2 3 4 5
P e r c e n t a g e o f r e s p o n s e s ( t o t a l = 1 0 0 )
5-point scale rang
(b) Event severity
very bad lt ---------------------------------- gt posive
0
10
20
30
40
1 2 3 4 5
P e r c e n t a g e o f r e s p o n s e s ( t o t a l = 1 0 0 )
Fig 4 Event-response matrices for the four country case studies The numbers in the column are percentage of total responses ranked from the most (left) to the least (right)
adopted
and
colour-coded
using
the
typology
presented
in
Table
1 Full
details
are
provided
in
Appendix
A
Table 4
Average number of responses per event at the community level
Country Community Mean Std Err [95 Conf Interval]
Fiji A 27 022 232 317
B 26 007 244 272
Ghana C 43 018 389 461
D 39 016 359 421
Sri
Lanka
E
55
020
514
594F 76 026 707 809
Vietnam G 34 012 319 367
H 35 019 308 383
Total
(N
=
1868)
46
005
451
474
C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170 159
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
Resilience outcomes were explored using psychometric tech-
niques where households were asked to self-assess the degree of
recovery they managed to achieve for each of the adverse events
they had experienced in the past (see details in Table 2) The
answers provided by the respondents to the 1047297rst two questions of
the resilience analysis (self-recovery from past event and self-
recovery compared to the rest of the community) were used to
create a resilience index (RI) computed as the product of the two
scores As a result of the calculation process RI is an integer varying
between 1 and 30 where low values indicate low level of resilienceto a speci1047297c event while higher values indicate higher levels of
resilience
We then used this resilience index to explore the last remaining
working hypothesis of this research that is that
lsquosocial capital is
importantrsquo- ie the (intuitive) idea that households or communi-
ties characterized by higher level of social capital are able to draw
on social capital to help themselves (and others) in the aftermath
of an adverse event To analyse the resilience outcomes and explore
in particular this last hypothesis a three-level mixed effect linear
model was run where the resilience index was tested against a
series of 1047297xed and random factors used as independent explana-
tory variables Because the communities are nested within the
countries a three-level (hierarchical) model was
1047297tted with
random intercepts at both country and community-within-
country levels Random coef 1047297cients were also accounted for at
the country level on the Quality of Life (QoL) factors to re1047298ect
country speci1047297c effects More speci1047297cally the model was of the
form
RI vc frac14 b0 thorn b1Shockvc thorn b2Respvc thorn b3QoLvc thorn b4HH vc thorn g 1W c thorn g 2 Z vc thorn
evc
where the subscripts v and c hold for village (community) and
country respectively Shockvc is the covariate matrix for the
1047297xed
effect
b1 of the impacts of event e on individual household Respvc
is the covariate matrix for the 1047297xed effect b2 of the responses put in
places by the household QoLe is the covariate matrix for the
1047297xed
effect b3 of the Quality of Life scores recorded for each household
HH e is the matrix of variables and dummies controlling for
household characteristics W c is the covariate matrix for the cluster
random effect at the country level and Z vc is the covariate matrix
for the cluster random effect at the community level The details of
the different categories of variables included in the model are
provided in Table 6
Results of the model estimations including details of both
1047297xed and random effect speci1047297cations and diagnostic checking-
are presented in Table 7 The model highlights a series of important
1047297ndings First the degree of severity of the shock and the
disruptive impact on income are the twoshock variables that have
0
10
20
30
40
50
60
70
80
90
F o o d
E x p e n s e s
M o n e y
A s s e s t
S u p p o r t
C o l l a b o r a o n
D i v e r s i fi c a o n
M i g r a o n
E x i t
C h a n g e
I n c r e a s e
P e r c e n t a g e o f h o u s e h o l d s ( )
Response typology (Vietnam)
Boom 40
Top 40
0
01
02
03
04
05
06
07
F o o d
E x p e n s e s
M o n e y
A s s e t s
S u p p o r t
C o l l a b o r a o n
D i v e r s i fi c a o n
M i g r a o n
E x i t
C h a n g e
I n c r e a s e
P e r c e n t a g e o f h o u s e h o l d s ( )
Response typology (Fiji)Boom 40
Top 40
Fig 5 Comparative analysis of the responses adopted by the bottom (poorest) and top (wealthiest) 40 of the households when affected by the same event illustration
from Vietnam and Fiji Code of the responses
ldquoFoodrdquo = Reduce food consumption
ldquoExpensesrdquo = Reduce family general expenses
ldquoMoneyrdquo = Borrow money
ldquoAssetsrdquo = Sell
family assets
ldquoSupportrdquo= Seek for support from friends and peers
ldquoCollaborationrdquo= Develop new collaboration within the community
ldquoDiversi1047297cationrdquo = Invest in non-
1047297shery activities ldquoMigrationrdquo = Temporary permanently migration one or several members of the family ldquoExitrdquo = Exit the 1047297shery start a new joblivelihoodldquoChangerdquo = Change 1047297shing strategies
ldquoIncreaserdquo = Increase 1047297shing effort
160 C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
The type of responses adopted by households was included in
the model to test whether the level of resilience of households is
effectively in1047298uenced by those responses Amongst the 11 types of
responses tested three have statistically signi1047297cant signs engag-
ing
in
new
collaboration
(negative
sign
P
=
0001)
increasing1047297shing effort (positive P lt 00001) and quitting the
1047297shery
(negative P = 0047) The negative correlation found between
household resilience and the strategy that consists of forming new
collaboration may be dif 1047297cult to interpret as it can re1047298ect many
highly contextual factors The two others responses and the signs
of their correlations (one negative sign for leaving the sector and
one positive sign for increasing 1047297shing effort) are initially
disturbing but eventually not too surprising Disturbing
1047297rst
because this
1047297nding does not lead to the type of long-term
behaviours that appeal to policy makers and 1047297shery managers On
the contrary they would rather see 1047297shing effort reductions and
exit strategies more often adopted by
1047297shers in particular in the
context of the current world
1047297shery crisis Not surprising however
because this result is in line with what one could expect from
1047297sherfolks after an adverse event in the face of a long-term stress
(such
as
the
drop
in
income
following
a
continuous
decline
in
1047297shcatch) or a sudden need for cashrevenues (as a consequence of
eg destruction of 1047297shing gear induced by bad weather or the
need to pay health bills)
1047297shers are often observed to alter their
1047297shing activities to make up for these events usually by changing
adjusting their 1047297shing strategy (eg switching between targeted
species andor
1047297shing gear) or increasing their
1047297shing effort (eg
investing in more ef 1047297cient
1047297shing gear increasing the quantity of
gear used or increasing the number of days at sea) in an attempt to
generate more cash In that context it is not surprising that the
majority of 1047297shing households interviewed in this research
consider that their ability to
lsquobounce back following an adverse
event was enhanced when they increase their 1047297shing effort
Additionally given what we know about their strong sense of
identity
(Kelty
and
Kelty
2011
Trimble
and
Johnson
2013) but
alsothe importance of peer-pressure and reputation (see eg Beacuteneacute and
Tew1047297k 2001) quitting the 1047297shery would certainly be perceived by
many 1047297shers as a failure thus the negative correlation between
(perceived) resilience and leaving the sector
The next category of variables which was investigated through
the model was the Quality of Life indicators (see Table 3 for a
recall) A reasonable hypothesis although not explicitly formu-
lated in the
lsquoworking hypotheses section above- is that some of
these QoL indices may have a positive effect on the ability of
households to handle and recover from adverse events One can
indeed assume that households satis1047297ed in many of the
dimensions of wellbeing which they considers important (such
as say access to health services or to public infrastructure) may
feel better equipped to reactrespond to any particular event than
Table 5
Top comparison of propensities to adopt particular types of responses for households characterized by high (N = 224) and low (N = 235) subjective resilience Bottom
comparison of the two same groups in terms of asset levels education and age of the household head
Responses subjective
resilience
level
Mean [95 Conf
Interval]
test resulta
Coping strategies High 198 1840 2136 t = 43037 Pr(|T| gt |
t|) = 0000
Low 245 2311 2596
Social-relation-based strategies High 083 0738 0927 t = 05187 Pr(|T| gt |
t|) = 0604
Low 086 0787 0943
Fishing-related strategies High 083 0732 0935 t = 03267 Pr(|T| gt |
t|)
=
0744
Low 081 0715 0906
Non-1047297shery
strategies
High
067
0559
0794
t
=
35599
Pr(|T|
gt
|
t|) = 0000
Low 042 0341 0502
Household characteristics
Asset High 768 7218 8157 t = 08882 Pr(|T| gt |
t|) = 0374
Low 739 6938 7848
Education High 796 7338 8599 t = 10186 Pr(|T| gt |
t|)
=
0308
Low 750 6857 8147
Age High 4688 45377 48391 t = 01332 Pr(|T| gt |
t|) = 0894
Low 4702 45570 48482
p
lt 5
p
lt 1
p
lt 1
a mean difference unpaired t -test Ho Diff = 0 Ha diff 6frac14 0
C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170 161
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
diversif non 1047297sher diversi1047297cation dummy 1 = yes
exit_1047297sh exit the 1047297shery sector dummy 1 = yes
migrat migrate dummy 1 = yes
quality of life indices
index_incom
income
index
ordinal
variable
coded
[-6
+6]
ndash6
=
very
poor
+6
=
very
strong
index_livelih livelihood index ordinal variable coded [-6 +6] ndash6 = very poor +6 = very strongindex_housing housing and infrastructure index ordinal variable coded [-6 +6] ndash6 = very poor +6 = very strong
index_educ education index ordinal variable coded [-6 +6]
ndash6 = very poor +6 = very strong
index_soc social capital index ordinal variable coded [-6 +6]
ndash6 = very poor +6 = very strong
index_health health index ordinal variable coded [-6 +6] ndash6 = very poor +6 = very strong
ind_emp empowerment index ordinal variable coded [-6 +6]
ndash6 = very poor +6 = very strong
index_soc_cris social capital index in time of crisis
ndash6 = very poor +6 = very strong
index_emp_cris empowerment index in time of crisis
ndash6 = very poor +6 = very strong
index_spirit index of spirituality
ordinal variable coded [-6 +6]
ndash6 = very poor +6 = very strong
household characteristics
HH head sex sex of household head dummy 1 = female
HH
head
age
age
of
household
head
age
in
years
HH head educ level of education of the household head 0 = no education 20 = post-graduate level
HH size size of household number of members (not adjusted for age)
log_asset household assets (log-transformed) value of household assets (proxy for wealth level)
community
resiliencecomm_recov level of recovery of the community
a Fitting a three level model requires two random-effect equations one for level three (country) and one for level two (community) with i = 1 nvc 1047297rst level of
observation (households) nested within k = 1 8 s level cluster (community) nested within j = 1 4 third level cluster (country)
162 C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
community level in the same way than the QoL indices that is by
averaging the scores obtained at the individual household level)
The best correlation was obtained with the QoL index of social
capital in time of crisis (R 2= 077 F = 0004) see Fig 6- suggesting
that communities with higher social capital in time of crisis are
also characterized by higher level of resilience
5 Discussion
Resilience has been increasingly recognized as a potentially
useful concept to help practitioners academics and policy-makers
better understand the links between shocks response and longer-
term development outcomes (Constas et al 2014a Beacuteneacute et al
2014) Incorporating resilience alongside vulnerability analysis can
contribute an essential element to societal ability to better prepare
for future shocks and stressors This paper argues that improving
our understanding of what contributes to or constitutes peoplersquos
resilience requires not only the development and
1047297eld-testing of
robust and measurable indices (Beacuteneacute 2013 Constas et al 2014b)
but also a better insight into the social factors including
knowledge perceptions and motivations- that in1047298uence and affect
individual and collective capacity to respond to shocks and
stressors
Our analysis conducted in eight 1047297shery-dependent communi-
ties from Fiji Ghana Sri Lanka and Vietnam reveals a series of
notable results in relation to these questions In considering these
outcomes it is important to 1047297rst take stock of potential limitations
pitfalls or biases in the study methodology Given the nature of the
1047297ndings two potential issues require further consideration First is
the question of how representative our sampling methodology
was It could be argued for instance that the observed low adoption
rates of non-1047297shery strategiesndash and in particular the low score of
the
lsquoexiting the
1047297sheryrsquo was driven by our sampling method
underrepresenting these groups as those who had effectively left
the 1047297shery were not included in the sample
The FGDs that preceded the household survey speci1047297cally
addressed this issue In Sri Lanka for instance the opening question
prompted participants (both men and women) to discuss whether
ldquo1047297shers in their community had ever left 1047297sheries due to their
inability to cope with adverse eventsrdquo The answer was that it
generally does not happen with the notable exception of someyoung
1047297shers who attempted to migrate to Australia through
illegal means If it occurred exiting the 1047297shery was said to be
temporary ldquothey may leave the village or 1047297shing but will come
back when the situation is favourablerdquo In Vietnam the sampling
was speci1047297cally designed to cover both
1047297shers and ex-1047297shers in
proportions represented in the community As a result 9 ex-1047297shers
were included in the sample Overall therefore although we were
unable to conceive of a completely representative sampling design
(in the statistical sense) the parallel information that was collected
in the FGDs and the individual households converge to suggest that
exiting the
1047297shery was not an option envisaged by the members of
these different communities and consequently that our sampling
was not too severely biased
0
2
4
6
8
10
12
14
16
-05 05 15 25
C o m m u n i t y l e v e l r e s i l i
e n c e i n d e x
Community level social capital in me of crisis
Fiji
Ghana
Sri Lanka
Vietnam
Fig 6 Correlation between social capital in time of crisis and resilience index
across the eight communities The straight line represents the linear relation
(R 2 = 077 F = 0004) and the bars are 95 con1047297dence intervals for each community
Random-effects parameters St Dev Std Err [95 Conf Interval]
country level
index_incom 043 024 0146 1266
index_livelih 051 027 0175 1464
index_housing 013 013 0018 0962
index_soc 039 024 0119 1303
index_soc_cris
078
038
0300
2009index_educ 015 013 0028 0834
const 090 067 0209 3861
community level
const 032 026 0066 1534
residuals 277 008 2617 2923
LR test vs linear regression chi2(7) = 3916 Prob gt chi2= 0000
p
lt 5
p
lt
1 p lt 1ma Fitting a three level model requires two random-effect equations one for level three (country) and one for level two (community) with i = 1 nvc 1047297rst level of
observation
(households)
nested
within
k
=
1
8
second
level
cluster
(community)
nested
within
j
=
1
4
third
level
cluster
(country)b The likelihood-ratio (LR) test comparing the nested mixed-effects model with the corresponding 1047297xed effect model con1047297rms the appropriate use of the mixed effect
model (chi2(7) = 3916 Prob gt chi2= 0000) and the Wald test con1047297rms that the independent variables are valid predictors (Wald chi2(45) = 59414 Prob gt chi2= 0000) A
speci1047297cation test performed on the 1047297xed effect model using a Pregibonrsquos goodness-of-link test shows good results (t = 077 P gt |t| = 0439)
c The dummy variables sev_event3 cat_event2 predict2 and comm_recov3 were omitted from the 1047297xed effect component for estimation purpose
Table 7 (Continued)
164 C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
The second potential limitation in our methodology relates to
the way the level of resilience of the households was assessed
While psychometric measurements are reliable and their results
replicable and testable when correctly implemented (Vigderhous
1977) one could fear that their use in the speci1047297c case of resilience
measurement could be subject to the effect of adaptive preference
that is the deliberate or re1047298exive process by which people adjust
their expectations and aspirations when trying to cope with
deterioration in living conditions (see eg Nussbaum 2001 Teschl
and Comim 2005) In our case this means that households
undergoing a degree of adaptive preference could have over-
estimated their ability to recover Although this risk is present we
tried to mitigate (or to reduce) it by introducing a qualifying
element in each of the coded answers of the resilience question-
naire so that respondents would have to associate the
1047297rst part of
their answer ldquoI have fully recoveredrdquo with a particular lsquoframe of
reference or quali1047297er (eg ldquoand it was not too dif 1047297cultrdquo) This frame
determined how they comprehend the questions being asked and
reduced the risk of the respondent simply relying on emotional
elements to answer these questions
Keeping in mind these potential limitations we now turn to
what we consider the most notable results of this research First is
the
lsquocumulative and continuous effect of shocks and stressors
whereby the impacts and disturbance of sequential shocksstressors and trends during the last 1047297ve years combine and
coalesce to create a constant non-stop stress We saw that the
nature and the source of events that were identi1047297ed by the
respondents in the four countries are all highly varied and
composite and reveal no speci1047297c clear pattern The events are a
combination of idiosyncratic and covariant sudden shocks and
long-term continuous trends Some are predictable while others
are totally unexpected All affect households simultaneously and
on an almost continuous basis The data suggests in particular that
on average households are hit by a new event every 16 months
This result calls into questions the framework generally used to
conduct shock or vulnerability assessment Often the approach has
been to disaggregate the problems people face and focus on single
threats such as eg 1047298ood or increase in food prices in order todevelop a clearer understanding of the impact of these particular
shocks and the ways people respond to them This approach has
been challenged however by a growing number of scholars who
argue that the reality households face on a daily basis is not linear
and mono-dimensional (OrsquoBrien and Leichenko 2000 Eriksen and
Silva 2009 Quinn et al 2011 McGregor 2011) Instead they argue
risks and vulnerability are often the product of multiple stressors
(Turner et al 2003 OrsquoBrien et al 2009) where social economic
political and biophysical factors interact combine and reinforce
each other to create a complex and dynamic multi-stressor multi-
shock environment (Reid and Vogel 2006 Adger 2006) Our
results corroborate this new interpretation
In line with this our analysis also shows that most households
engage in a suite of responses to a given shock On average
households adopted more than 4 types of responses to a particular
event This last result does not simply imply a rethinking of the way
shock or vulnerability assessments are conceptualized and
conducted see eg Turner et al (2003) or Leichenko and OrsquoBrien
(2008) It also demonstrates that the mental model (shock
gt response gt recovery) which is widely accepted in the
resilience literature is too simplistic and possibly misleading in
the sense that a state of (full) recovery may not exist This is at least
what was observed for the households included in our research
these households did not seem to have the chance or the time to
fully recover from one particular event before being affected by the
next Instead they were caught in what we could characterize as ldquoaconstant state of incomplete recoveringrdquo from new shocks and
stressors as illustrated in Fig 7
The next entry point in this discussion is wealth Our mixed
effect model (Table 7) shows that wealth was positively correlated
with household resilience Wealth has been identi1047297ed in the
literature as a key factor in strengthening the resilience of
households (Prowse and Scott 2008 WFP 2013) Analysis of
rural Ethiopian households hit by drought for instance showed that
while better-off households could sell livestock to smooth
consumption the poorer often tried to hold on to their livestock
at the expense of food consumption to preserve their options for
rebuilding herds The same study also shows that in the aftermath
of the hurricane Mitch in Honduras the relatively wealthy
households were able to rebuild their lost assets faster than thepoorest households for whom the effects of the hurricane were of
longer duration and felt much more acutely (Carter et al 2007) In
Fig 7 Left Current conceptualisation of resilience shock gt response gt recovery as presented in the literature [here redrawn from Carter et al 2007] Right actual
situation where the multi-stressor multi-shock environment induces that households are in a trajectory of continual and incomplete recovery Not represented here are the
multi-response
strategies
put
in
place
by
households
to
respond
to
these
adverse
events
C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170 165
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
disaster resilience National Disaster Resilience Roundtable Report 20September 2012 Melbourne Australia 36 p
Adger NW Dessai S Goulden M Hulme M Lorenzoni I Nelson DR Naess LO Wolf J Wreford A 2009 Are there social limits to adaptation to climatechange
Clim
Change
93
335ndash354Adger WN 2003 Social capital collective action and adaptation to climate
change Econ Geogr 79 (4) 387ndash404Adger WN 2006 Vulnerability Glob Environ Change 16 268ndash281Aldrich D 2010 Fixing recovery social capital in post-Crisis resilience J Homeland
Secur 6 1ndash10Ayers
J
Forsyth
T
2009
Community-based
adaptation
to
climate
changestrengthening resilience through development Environment 51 23ndash31
Beacuteneacute C Tew1047297k A 2001 Fishing effort allocation and 1047297shermenrsquos decision-makingprocess in a multi-species small-scale 1047297shery analysis of the conch and lobster1047297shery in Turks and Caicos Islands Hum Ecol 29 (2) 157ndash186
Beacuteneacute
C
Evans
L
Mills
D
Ovie
S
Raji
A
Ta1047297da
A
Kodio
A
Sinaba
F
Morand
PLemoalle J Andrew N 2011 Testing resilience thinking in a poverty contextexperience from the Niger river basin Glob Environ Change 21 (4) 1173ndash1184
Beacuteneacute C Godfrey-Wood R Newsham A Davies M2012 Resilience new utopia ornew tyranny
ndash Re1047298ection about the potentials and limits of the concept of
resilience
in
relation
to
vulnerability
reduction
programmes
IDS
Working
Paperno 405 Institute of Development Studies Brighton 61 p
Beacuteneacute C Newsham A Davies M Ulrichs M Godfrey-Wood R 2014 Resiliencepoverty and development J Int Dev 26 598ndash623
Beacuteneacute C Waid J Jackson-deGraffenried M Begum A Chowdhury M Skarin VRahman A Islam N Mamnun N Mainuddin K Shah MA 2015a Impact of climate-related
shocks
and
stresses
on
nutrition
and
food
security
in
ruralBangladesh Dhaka World Food Programme 119 p
Beacuteneacute C Frankenberger T Nelson S 2015b Design monitoring and evaluation of resilience interventions conceptual and empirical considerations IDS WorkingPaper no459 Institute of Development Studies 23 p
Beacuteneacute
C
2013
Towards
a
quanti1047297able
measure
of
resilience
IDS
Working
Paper
434Institute of Development Studies Brighton 27 p
Bandura A 1977 Self-ef 1047297cacy toward a unifying theory of behavioral changePsychol Rev 84 191ndash215
Baulch R Hoddinott J 2000 Economic mobility and poverty dynamics indeveloping countries J Dev Stud 36 (6) 1ndash23
Belhabib
D
Sumaila
UR
Pauly
D
2015
Feeding
the
poor
contribution
of
WestAfrican 1047297sheries to employment and food security Ocean Coast Manage 11172ndash81
Berkes F Folke C 1998 Linking social and ecological systems for resilience andsustainability In Berkes F Folke C (Eds) Linking Social and EcologicalSystems Management Practices and Social Mechanisms for Building ResilienceCambridge University Press Cambridge pp 1ndash25
Bernier Q Meinzen-Dick R 2014 Resilience and social capital Building Resiliencefor Food and Nutrition Security Conference Paper No 4 International FoodPolicy Research Institute Washington DC 26 p
Bhattamishra R Barrett C 2010 Community-Based risk managementarrangements a review World Dev 38 (7) 923ndash932
Boarini R Kolev A McGregor JA 2014 Measuring well-being and progress incountries at different stages of development towards a more universalconceptual framework OECD Working Paper No 235 Organisation forEconomic Co-operation and Development Development Center
ndash Better Life
Initiative Paris 59 p
Boyd E Osbahr H Ericksen P Tompkins E Carmen Lemos M Miller F 2008Resilience and
lsquoclimatizingrsquo development examples and policy implicationsDevelopment 51 390ndash396
Cam1047297eld
L
McGregor
JA
2005
Resilience
and
wellbeing
in
developing
countriesIn Ungar M (Ed) Handbook for Working with Children and Youth Pathwaysto Resilience Across Cultures and Contexts Sage Publications Thousand OaksCA
Cam1047297eld
L
Ruta
D
2007
Translation
is
not
enough
using
the
Global
PersonGenerated Index (GPGI) to assess individual quality of life in BangladeshThailand and Ethiopia Qual Life 16 (6) 1039ndash1051
Carter M Little P Mogues T Negatu W 2007 Poverty traps and natural disastersin Ethiopia and Honduras World Dev 35 (5) 835ndash856
Cleaver
F
2005
The
inequality
of
social
capital
and
the
reproduction
of
chronicpoverty World Dev 33 (6) 893ndash906
Constas M Frankenberger T Hoddinott J 2014a Resilience measurementprinciples toward an agenda for measurement design Resilience MeasurementTechnical Working Group Technical Series No 1 Food Security informationNetwork Rome
Constas MT Frankenberger J Hoddinott N Mock D Romano C Beacuteneacute DMaxwell 2014b A common analytical model for resilience measurementcausal framework and methodological options Food Security InformationNetwork (FSIN) Technical Series No 2 World Food Programme Rome
Coulthard S 2011 More than just access to 1047297sh the pros and cons of 1047297sherparticipation
in
a
customary
marine
tenure
(Padu)
system
under
pressure
MarPolicy 35 405ndash412
DFID 2011 De1047297ning Disaster Resilience A DFID Approach Paper Department forInternational Development London pp 20
Dercon S Hoddinott J Woldehanna T 2005 Shocks and consumption in 15ethiopian
villages
1999ndash2004
J
Afr
Econ
14
(4)
559ndash585Dercon S 1996 Risk crop choice and savings evidence from Tanzania Econ Dev
Cult Change 44 (3) 485ndash513Duit A Galaz V Eckerberg K 2010 Governance complexity and resilience Glob
Environ Change 20 (3) 363ndash368Eriksen
SEH
Silva
JA
2009
The
vulnerability
context
of
a
savannah
area
inMozambique household drought coping strategies and responses to economicchange Environ Sci Policy 12 (1) 33ndash52
Fafchamps M Lund S 2003 Risk-Sharing networks in rural Philippines J DevEcon 71 (2) 261ndash287
Frankenberger T Nelson S 2013 Background Paper for the Expert Consultation onResilience
Measurement
for
Food
Security
TANGO
International
Rome
Foodand Agricultural Organization and World Food Program
Heltberg R Siegel PS Jorgensen SL 2009 Addressing human vulnerability toclimate change towards a
lsquono-regretsrsquo approach Glob Environ Change 19 89ndash99
Hoddinott
J
Dercon
S
Krishnan
P
2009
Networks
and
informal
mutual
supportin 15 ethiopian villages a description In Kirsten JF Dorward AR Poulton CVink N (Eds) Institutional Economics Perspectives on African AgriculturalDevelopment International Food Policy Research Institute Washington DC pp273ndash286
Hoddinott
J
2006
Shocks
and
their
consequences
across
and
within
households
inRural Zimbabwe J Dev Stud 42 (2) 301ndash321
Intergovernmental Panel on Climate Change (IPCC) 2012 In Field CB Barros VStocker TF Qin D Dokken DJ Ebi KL Mastrandrea MD Mach KJPlattner G-K Allen SK Tignor MMidgley PM (Eds) Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation A SpecialReport of Working Groups I and II of the Intergovernmental Panel on ClimateChange Cambridge University Press Cambridge UK
Jackson T 2005 Motivating sustainable consumptionmdasha review of evidence onconsumer behaviour and behavioural change A Report to the Sustainable
Event type (Vietnam) Reduce
expenditures
Borrow
money
Reduce
Food
Change
1047297shing
strategy
Get
support
Increase
1047297shing
effort
Diversi1047297cation Seek new
collaboration
Migration Exit the
1047297shery
Sell
assets
Total
Others (aggregated) 4 7 4 6 3 0 1 3 0 0 2 30
Erosion 2 4 2 1 6 2 2 2 3 1 25
Catch reduced
suddenly
8 4 6 7 1 2 4 2 34
Gears lost 10 18 6 5 1 2 1 43
Cold wind prolongs 15 7 11 3 1 7 2 46
Typhoon
12
11
10
2
4
2
3
5
4
1
1
55
Illness
11 14
6
2
11
2
2
4
1
1
2
56Food price increase 20 17 19 2 8 5 1 72
Input price increase
continuously
47 39 33 21 40 5 6 16 1 208
Big boats compete
ground and catch
54 39 32 40 9 19 11 15 8 3 2 232
Catch
reduced
continuously
102
70
80
63
22
51
51
25
23
17
6
510
Total 285 230 209 152 105 91 87 75 39 23 15 1311
C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170 169
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
Development Research Network Centre for Environmental StrategiesUniversity of Surrey
Jones L Boyd E 2011 Exploring social barriers to adaptation insights fromWestern Nepal Glob Environ Change 21 (4) 1262ndash1274
Kallstrom HN Ljung M 2005 Social sustainability and collaborative learningAmbio 34 376ndash382
Kelty R Kelty R 2011 Human dimensions of a 1047297shery at a crossroads resourcevaluation identity and way of life in a seasonal 1047297shing community Soc NatResour
24
(4)
334ndash348Klein RJT Nicholls RJ Thomalla F 2003 Resilience to natural hazards how
useful is this concept Environ Hazards 5 35ndash45
Krosnick
JA
Fabrigar
LR
1997
Designing
rating
scales
for
effective
measurementin surveys In Lyberg L Biemer P Collins M de Leeuw E Dippo C SchwarzN
Trewin
D
(Eds)
Survey
Measurement
and
Process
Quality
John
Wiley
andSons Inc New York NY pp 141ndash164
Leichenko R OrsquoBrien K 2008 Environmental Change and Globalization DoubleExposures Oxford University Press New York
Marschke M Berkes F 2006 Exploring Strategies that build livelihood resiliencea case from Cambodia Ecol Soc 11 (1) httpwwwecologyandsocietyorgvol11iss1art42
McGregor JA Cam1047297eld L Woodcock A 2009 Needs wants and goals wellbeingquality
of
life
and
public
policy
Appl
Res
Qual
Life
4
135ndash154McGregor JA 1994 Village credit and the reproduction of poverty in rural
Bangladesh In Acheson J (Ed) Economic Anthropology and the NewInstitutional Economics University Press of AmericaSociety for EconomicAnthropology Washington pp 261ndash281 (Chapter)
McGregor
JA
2011
Reimagining
development
through
the
crisis
watch
initiative
IDS Bull 42 (5) 17ndash23McLaughlin P Dietz T 2007 Structureagency and environment toward an
integrated perspective on vulnerability Glob Environ Change 39 (4) 99ndash111Meyer MA 2013 Social capital and resilience in the context of disaster social
capital
and
collective
ef 1047297cacy
for
disaster
resilience
connecting
individualswith communities and vulnerability with resilience in hurricane-pronecommunities in Florida PhD Dissertation Department of sociology Coloradostate University Fort Collins Colorado (311 p)
Mills DJ Adhuri D Phillips M Ravikumar B Padiyar AP 2011 Shocks recoverytrajectories and resilience among aquaculture-dependent households in post-tsunami
Aceh
Indonesia
Local
Environ
Int
J
Justice
Sustain
16
(5)
425ndash444Morduch J 1995 Income smoothing and consumption smoothing J Econ
Perspect 9 (3) 103ndash114Morris S Carletto C Hoddinott J Christiaensen L 2000 J Epidemiol Commun
Health 54 381ndash387Myers
RA
Worm
B
2003
Rapid
worldwide
depletion
of
predatory 1047297sh
communities Nature 423 280ndash283Nakagawa Y Shaw R 2004 Social capital a missing link to disaster recovery Int J
Mass
Emerg
Disasters
22
(1)
5ndash
34Nussbaum MC 2001 Adaptive preferences and womenrsquos options Econ Philos 1767ndash88
Oslashstergaard N Reenberg A 2010 Cultural barriers to climate change adaptation acase study from Northern Burkina Faso Glob Environ Change 20 (1) 142ndash152
OrsquoBrien K Leichenko R 2000 Double exposure assessing the impacts of climatechange within the context of economic globalization Glob Environ Change 10221ndash232
OrsquoBrien K Eriksen S Sygna L Naess LO 2006 Questioning complacencyclimate change impacts vulnerability and adaptation in Norway AMBIO JHum Environ 35 (2) 50ndash56
OrsquoBrien K Quilan T Ziervogel G 2009 Vulnerability interventions in the contextof multiple stressors lessons from the Southern Africa vulnerability initiative(SAVI) Environ Sci Policy 12 23ndash32
OrsquoRiordan T Jordan A 1999 Institutions climate change and cultural theorytowards a common analytical framework Glob Environ Change 9 (2) 81ndash93
Pain A Levine S 2012 A conceptual analysis of livelihoods and resilienceaddressing the
lsquoinsecurity of agency HPG Working Paper OverseasDevelopment Institute Humanitarian Policy Group London
Pauly D Christensen V Dalsgaard Froese JR Torres F 1998 Fishing downmarine food webs Science 279 (5352) 860ndash863
Pelling M Manuel-Navarrete D 2011 From resilience to transformation theadaptive cycle in two Mexican urban centersEcol Soc 16 (2)11 (online) httpwwwecologyandsocietyorgvol16iss2art11
Prowse
M
Scott
L
2008
Assets
and
adaptation
an
emerging
debate
IDS
Bull
39(4) 42ndash52
Putzel J 1997 Accounting for the lsquodark sidersquo of social capital reading Robert
Putnam
on
democracy
J
Int
Dev
9
(7)
939ndash949
Quinn CH Ziervogel G Taylor A Takama T Thomalla F 2011 Coping withmultiple
stresses
in
rural
South
Africa
Ecol
Soc
16
(3)
doihttpdxdoiorg105751ES-04216-160302
Reid P Vogel C 2006 Living and responding to multiple stressors in South Africamdashglimpses from KwaZulu-Natal Glob Environ Change 16 (2) 195ndash206
Roncoli C Ingram K Kirshen P 2001 The costs and risks of coping with droughtlivelihood
impacts
and
farmersrsquo
responses
in
Burkina
Faso
Clim
Res
19
119ndash132
Schwarz AM Beacuteneacute C Bennett G Boso D Hilly Z Paul C Posala R Sibiti SAndrew N 2011 Vulnerability and resilience of rural remote communities toshocks and global changes empirical analysis from the Solomon Islands GlobEnviron Change 21 1128ndash1140
Sinha
S
Lipton
M
Yaqub
S
2002
Poverty
and
damaging 1047298uctuations
how
dothey relate J Asian Afr Stud 37 (2) 186ndash243
Tansey J OrsquoRiordan T 1999 Cultural theory and risk a review Health Risk Soc 171ndash90
Teschl M Comim F 2005 Adaptive preferences and capabilities somepreliminary
conceptual
explorations
Rev
Soc
Econ
63
(2)
229ndash247
Trimble M Johnson D 2013 Artisanal 1047297shing as an undesirable way of life Theimplications for governance of 1047297shersrsquo wellbeing aspirations in coastal Uruguayand southeastern Brazil Mar Policy 37 37ndash44
Turner BL Kasperson RE Matson P McCarthy JJ Corell RW Christensen LEckley
N
Kasperson
JX
Luers
A
Martello
ML
Polsky
C
Pulsipher
ASchiller A 2003 A framework for vulnerability analysis in sustainabilityscience Proc Natl Acad Sci 100 (14) 8074ndash8079
Vigderhous G 1977 The level of measurement and
lsquoPermissiblersquo statistical analysisin social research Pac Sociol Rev 20 (1) 61ndash72
WFP 2013 Building Resilience Through Asset Creation Resilience and PreventionUnit
Policy
Programme
and
Innovation
Division
World
Food
Program
Rome(23 p)
Walker B Carpenter S Anderies J Abel N Cumming GS Janssen M Lebel LN J Peterson GD Pritchard R 2002 Resilience management in social-ecological systems a working hypothesis for a participatory approach ConservEcol
6
(1)
14Weber EU 2010 What shapes perceptions of climate change Clim Change 1 (3)
332ndash342
Wolf
J
Adger
WN
Lorenzoni
I
Abrahamson
V
Raine
R
2010
Social
capitalindividual responses to heat waves and climate change adaptation an empiricalstudy
of
two
UK
cities
Glob
Environ
Change
20
44ndash52Wood G 2003 Staying secure staying poor the Faustian bargain World Dev 31
(3) 455ndash471World Bank 2011 Building Resilience and Opportunities World Bankrsquos Social
Protection and Labour Strategy 2012ndash2022 World Bank Washington DCYamano T Alderman H Christiaensen L 2003 Child Growth Shocks and Food
Aid in Rural Ethiopia World Bank Washington DCZimmerman F Carter M 2003 Asset smoothing consumption smoothing and the
reproduction of inequality under risk and subsistence constraints J Dev Econ71 233ndash260
von Grebmer K Headey D Beacuteneacute C Haddad L et al 2013 Global Hunger IndexThe Challenge of Hunger Building Resilience to Achieve Food and NutritionSecurity Welthungerhilfe International Food Policy Research Institute andConcern Worldwide Bonn Washington DC and Dublin
170 C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
when all events are aggregated households are hit by a new event
of some kind every 485 days that is every 16 months
42 Household response analysis
The next step was to document and analyse the various types of
strategies that households employed in the face of shocks and
stressors In the resilience analysis framework (Fig 1) this
corresponds to the
lsquoresponse analysisrsquo component
Fig 4 presents the event-response matrices for the four country
case studies (computed for the ten most cited events per country)
The colour codes correspond to the four categories described in
Table 1 coping strategies social-relation based strategies 1047297shery-
related strategies and non-1047297shery-related strategies
The matrices show that coping strategies are the most frequent
responses put in place by households Amongst coping strategies
reduction of food consumption and reduction of general expenses
were commonly adopted while asset selling was notable for being
seldom adopted except in Ghana Beyond the generic pattern of
0 005 01 015 02 025 03 035
Others
High de
Destruconlossthe of fishing gear
Sudden change in sea condion
Slow increase in input prices
Major health problem
Death
Flood
Rapid (peak) increase in input prices
Decline in fish price
Sudden decli ne in catch
Slow decline in catch
Slow increase in food prices
Important change in fishing techniques
Any other fishery rela ted issue
unpredictable c hanges in weather
Hurricane
Percentage (total = 100)
Fiji
ST
MT
LT
0 005 01 015 02 025 03
Others
Increase in Food Price
Storm and strong winds
Unpred weather change
Accident Disability
Change in sea condion
Loss of financial assets
Loss of other assetsLoss fishing ground
Flood
Fish price increase
Sick family member
Death of family member
Destrucon The Loss gear
Input prices increase
Change in fishing techniques
Fuel shortage
Slow decline in catch
Percentage (total = 100)
Ghana
ST
MT
LT
0 005 01 015 0
Others
Slow but constant increase in input prices
Death of a family m ember
Other major weather event
Sudden change in sea condion
Flood
Sudden decline in catch
Loss of other assets other than fishing gear
Major health problem (sickness)
Decline in fish price
More unpredictable changes in weather paern
Important change in fishing techniquesSlow decline in catch
Limitaons-Harbour
New constraining fishing regulaon
Destruconlossthe of fishing gear
Rapid (peak) increase in input prices
Hurricane tropical storm
Perccentage (total = 100)
Sri Lanka
ST
MT
LT
0
005
01
015
02
025
03
035
04
045
Others
Lost assets
Accident
Erosion
Catch r educed suddently
Gears lost
Cold wind prolongs
Typhoon
Illness
Food price increase
Input price increa se connuously
Big boats compete ground and catch
Catch reduced connuously
Percentage (total = 100)
Vietnam
ST
MT
LT
Fig 2 Adverse event inventory for the four countries Events have been grouped and colour-coded into three categories short and unpredictable shocks (ST) (ii) medium-
term stressors that last several months andor are recurrent (MT) and (iii) long-term trends (LT)
0 10 20 30
Annually
On a connuous (daily) basis
Every 5 years
Bi-annually
Quarterly basis
Weekly basis
Monthly basis
Every two-year
Every 10 years
Every 20 year or less oen
Percentage of responses (total = 100)
(c) Event frequency
0
10
20
30
40
50
60
70
1 2 3 4 5
P e r c e n t a g e o f r e s p o n s e s ( t o t a l = 1 0 0 )
5-point scale rang
(b) Event severity
very bad lt ---------------------------------- gt posive
0
10
20
30
40
1 2 3 4 5
P e r c e n t a g e o f r e s p o n s e s ( t o t a l = 1 0 0 )
Fig 4 Event-response matrices for the four country case studies The numbers in the column are percentage of total responses ranked from the most (left) to the least (right)
adopted
and
colour-coded
using
the
typology
presented
in
Table
1 Full
details
are
provided
in
Appendix
A
Table 4
Average number of responses per event at the community level
Country Community Mean Std Err [95 Conf Interval]
Fiji A 27 022 232 317
B 26 007 244 272
Ghana C 43 018 389 461
D 39 016 359 421
Sri
Lanka
E
55
020
514
594F 76 026 707 809
Vietnam G 34 012 319 367
H 35 019 308 383
Total
(N
=
1868)
46
005
451
474
C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170 159
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
Resilience outcomes were explored using psychometric tech-
niques where households were asked to self-assess the degree of
recovery they managed to achieve for each of the adverse events
they had experienced in the past (see details in Table 2) The
answers provided by the respondents to the 1047297rst two questions of
the resilience analysis (self-recovery from past event and self-
recovery compared to the rest of the community) were used to
create a resilience index (RI) computed as the product of the two
scores As a result of the calculation process RI is an integer varying
between 1 and 30 where low values indicate low level of resilienceto a speci1047297c event while higher values indicate higher levels of
resilience
We then used this resilience index to explore the last remaining
working hypothesis of this research that is that
lsquosocial capital is
importantrsquo- ie the (intuitive) idea that households or communi-
ties characterized by higher level of social capital are able to draw
on social capital to help themselves (and others) in the aftermath
of an adverse event To analyse the resilience outcomes and explore
in particular this last hypothesis a three-level mixed effect linear
model was run where the resilience index was tested against a
series of 1047297xed and random factors used as independent explana-
tory variables Because the communities are nested within the
countries a three-level (hierarchical) model was
1047297tted with
random intercepts at both country and community-within-
country levels Random coef 1047297cients were also accounted for at
the country level on the Quality of Life (QoL) factors to re1047298ect
country speci1047297c effects More speci1047297cally the model was of the
form
RI vc frac14 b0 thorn b1Shockvc thorn b2Respvc thorn b3QoLvc thorn b4HH vc thorn g 1W c thorn g 2 Z vc thorn
evc
where the subscripts v and c hold for village (community) and
country respectively Shockvc is the covariate matrix for the
1047297xed
effect
b1 of the impacts of event e on individual household Respvc
is the covariate matrix for the 1047297xed effect b2 of the responses put in
places by the household QoLe is the covariate matrix for the
1047297xed
effect b3 of the Quality of Life scores recorded for each household
HH e is the matrix of variables and dummies controlling for
household characteristics W c is the covariate matrix for the cluster
random effect at the country level and Z vc is the covariate matrix
for the cluster random effect at the community level The details of
the different categories of variables included in the model are
provided in Table 6
Results of the model estimations including details of both
1047297xed and random effect speci1047297cations and diagnostic checking-
are presented in Table 7 The model highlights a series of important
1047297ndings First the degree of severity of the shock and the
disruptive impact on income are the twoshock variables that have
0
10
20
30
40
50
60
70
80
90
F o o d
E x p e n s e s
M o n e y
A s s e s t
S u p p o r t
C o l l a b o r a o n
D i v e r s i fi c a o n
M i g r a o n
E x i t
C h a n g e
I n c r e a s e
P e r c e n t a g e o f h o u s e h o l d s ( )
Response typology (Vietnam)
Boom 40
Top 40
0
01
02
03
04
05
06
07
F o o d
E x p e n s e s
M o n e y
A s s e t s
S u p p o r t
C o l l a b o r a o n
D i v e r s i fi c a o n
M i g r a o n
E x i t
C h a n g e
I n c r e a s e
P e r c e n t a g e o f h o u s e h o l d s ( )
Response typology (Fiji)Boom 40
Top 40
Fig 5 Comparative analysis of the responses adopted by the bottom (poorest) and top (wealthiest) 40 of the households when affected by the same event illustration
from Vietnam and Fiji Code of the responses
ldquoFoodrdquo = Reduce food consumption
ldquoExpensesrdquo = Reduce family general expenses
ldquoMoneyrdquo = Borrow money
ldquoAssetsrdquo = Sell
family assets
ldquoSupportrdquo= Seek for support from friends and peers
ldquoCollaborationrdquo= Develop new collaboration within the community
ldquoDiversi1047297cationrdquo = Invest in non-
1047297shery activities ldquoMigrationrdquo = Temporary permanently migration one or several members of the family ldquoExitrdquo = Exit the 1047297shery start a new joblivelihoodldquoChangerdquo = Change 1047297shing strategies
ldquoIncreaserdquo = Increase 1047297shing effort
160 C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
The type of responses adopted by households was included in
the model to test whether the level of resilience of households is
effectively in1047298uenced by those responses Amongst the 11 types of
responses tested three have statistically signi1047297cant signs engag-
ing
in
new
collaboration
(negative
sign
P
=
0001)
increasing1047297shing effort (positive P lt 00001) and quitting the
1047297shery
(negative P = 0047) The negative correlation found between
household resilience and the strategy that consists of forming new
collaboration may be dif 1047297cult to interpret as it can re1047298ect many
highly contextual factors The two others responses and the signs
of their correlations (one negative sign for leaving the sector and
one positive sign for increasing 1047297shing effort) are initially
disturbing but eventually not too surprising Disturbing
1047297rst
because this
1047297nding does not lead to the type of long-term
behaviours that appeal to policy makers and 1047297shery managers On
the contrary they would rather see 1047297shing effort reductions and
exit strategies more often adopted by
1047297shers in particular in the
context of the current world
1047297shery crisis Not surprising however
because this result is in line with what one could expect from
1047297sherfolks after an adverse event in the face of a long-term stress
(such
as
the
drop
in
income
following
a
continuous
decline
in
1047297shcatch) or a sudden need for cashrevenues (as a consequence of
eg destruction of 1047297shing gear induced by bad weather or the
need to pay health bills)
1047297shers are often observed to alter their
1047297shing activities to make up for these events usually by changing
adjusting their 1047297shing strategy (eg switching between targeted
species andor
1047297shing gear) or increasing their
1047297shing effort (eg
investing in more ef 1047297cient
1047297shing gear increasing the quantity of
gear used or increasing the number of days at sea) in an attempt to
generate more cash In that context it is not surprising that the
majority of 1047297shing households interviewed in this research
consider that their ability to
lsquobounce back following an adverse
event was enhanced when they increase their 1047297shing effort
Additionally given what we know about their strong sense of
identity
(Kelty
and
Kelty
2011
Trimble
and
Johnson
2013) but
alsothe importance of peer-pressure and reputation (see eg Beacuteneacute and
Tew1047297k 2001) quitting the 1047297shery would certainly be perceived by
many 1047297shers as a failure thus the negative correlation between
(perceived) resilience and leaving the sector
The next category of variables which was investigated through
the model was the Quality of Life indicators (see Table 3 for a
recall) A reasonable hypothesis although not explicitly formu-
lated in the
lsquoworking hypotheses section above- is that some of
these QoL indices may have a positive effect on the ability of
households to handle and recover from adverse events One can
indeed assume that households satis1047297ed in many of the
dimensions of wellbeing which they considers important (such
as say access to health services or to public infrastructure) may
feel better equipped to reactrespond to any particular event than
Table 5
Top comparison of propensities to adopt particular types of responses for households characterized by high (N = 224) and low (N = 235) subjective resilience Bottom
comparison of the two same groups in terms of asset levels education and age of the household head
Responses subjective
resilience
level
Mean [95 Conf
Interval]
test resulta
Coping strategies High 198 1840 2136 t = 43037 Pr(|T| gt |
t|) = 0000
Low 245 2311 2596
Social-relation-based strategies High 083 0738 0927 t = 05187 Pr(|T| gt |
t|) = 0604
Low 086 0787 0943
Fishing-related strategies High 083 0732 0935 t = 03267 Pr(|T| gt |
t|)
=
0744
Low 081 0715 0906
Non-1047297shery
strategies
High
067
0559
0794
t
=
35599
Pr(|T|
gt
|
t|) = 0000
Low 042 0341 0502
Household characteristics
Asset High 768 7218 8157 t = 08882 Pr(|T| gt |
t|) = 0374
Low 739 6938 7848
Education High 796 7338 8599 t = 10186 Pr(|T| gt |
t|)
=
0308
Low 750 6857 8147
Age High 4688 45377 48391 t = 01332 Pr(|T| gt |
t|) = 0894
Low 4702 45570 48482
p
lt 5
p
lt 1
p
lt 1
a mean difference unpaired t -test Ho Diff = 0 Ha diff 6frac14 0
C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170 161
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
diversif non 1047297sher diversi1047297cation dummy 1 = yes
exit_1047297sh exit the 1047297shery sector dummy 1 = yes
migrat migrate dummy 1 = yes
quality of life indices
index_incom
income
index
ordinal
variable
coded
[-6
+6]
ndash6
=
very
poor
+6
=
very
strong
index_livelih livelihood index ordinal variable coded [-6 +6] ndash6 = very poor +6 = very strongindex_housing housing and infrastructure index ordinal variable coded [-6 +6] ndash6 = very poor +6 = very strong
index_educ education index ordinal variable coded [-6 +6]
ndash6 = very poor +6 = very strong
index_soc social capital index ordinal variable coded [-6 +6]
ndash6 = very poor +6 = very strong
index_health health index ordinal variable coded [-6 +6] ndash6 = very poor +6 = very strong
ind_emp empowerment index ordinal variable coded [-6 +6]
ndash6 = very poor +6 = very strong
index_soc_cris social capital index in time of crisis
ndash6 = very poor +6 = very strong
index_emp_cris empowerment index in time of crisis
ndash6 = very poor +6 = very strong
index_spirit index of spirituality
ordinal variable coded [-6 +6]
ndash6 = very poor +6 = very strong
household characteristics
HH head sex sex of household head dummy 1 = female
HH
head
age
age
of
household
head
age
in
years
HH head educ level of education of the household head 0 = no education 20 = post-graduate level
HH size size of household number of members (not adjusted for age)
log_asset household assets (log-transformed) value of household assets (proxy for wealth level)
community
resiliencecomm_recov level of recovery of the community
a Fitting a three level model requires two random-effect equations one for level three (country) and one for level two (community) with i = 1 nvc 1047297rst level of
observation (households) nested within k = 1 8 s level cluster (community) nested within j = 1 4 third level cluster (country)
162 C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
community level in the same way than the QoL indices that is by
averaging the scores obtained at the individual household level)
The best correlation was obtained with the QoL index of social
capital in time of crisis (R 2= 077 F = 0004) see Fig 6- suggesting
that communities with higher social capital in time of crisis are
also characterized by higher level of resilience
5 Discussion
Resilience has been increasingly recognized as a potentially
useful concept to help practitioners academics and policy-makers
better understand the links between shocks response and longer-
term development outcomes (Constas et al 2014a Beacuteneacute et al
2014) Incorporating resilience alongside vulnerability analysis can
contribute an essential element to societal ability to better prepare
for future shocks and stressors This paper argues that improving
our understanding of what contributes to or constitutes peoplersquos
resilience requires not only the development and
1047297eld-testing of
robust and measurable indices (Beacuteneacute 2013 Constas et al 2014b)
but also a better insight into the social factors including
knowledge perceptions and motivations- that in1047298uence and affect
individual and collective capacity to respond to shocks and
stressors
Our analysis conducted in eight 1047297shery-dependent communi-
ties from Fiji Ghana Sri Lanka and Vietnam reveals a series of
notable results in relation to these questions In considering these
outcomes it is important to 1047297rst take stock of potential limitations
pitfalls or biases in the study methodology Given the nature of the
1047297ndings two potential issues require further consideration First is
the question of how representative our sampling methodology
was It could be argued for instance that the observed low adoption
rates of non-1047297shery strategiesndash and in particular the low score of
the
lsquoexiting the
1047297sheryrsquo was driven by our sampling method
underrepresenting these groups as those who had effectively left
the 1047297shery were not included in the sample
The FGDs that preceded the household survey speci1047297cally
addressed this issue In Sri Lanka for instance the opening question
prompted participants (both men and women) to discuss whether
ldquo1047297shers in their community had ever left 1047297sheries due to their
inability to cope with adverse eventsrdquo The answer was that it
generally does not happen with the notable exception of someyoung
1047297shers who attempted to migrate to Australia through
illegal means If it occurred exiting the 1047297shery was said to be
temporary ldquothey may leave the village or 1047297shing but will come
back when the situation is favourablerdquo In Vietnam the sampling
was speci1047297cally designed to cover both
1047297shers and ex-1047297shers in
proportions represented in the community As a result 9 ex-1047297shers
were included in the sample Overall therefore although we were
unable to conceive of a completely representative sampling design
(in the statistical sense) the parallel information that was collected
in the FGDs and the individual households converge to suggest that
exiting the
1047297shery was not an option envisaged by the members of
these different communities and consequently that our sampling
was not too severely biased
0
2
4
6
8
10
12
14
16
-05 05 15 25
C o m m u n i t y l e v e l r e s i l i
e n c e i n d e x
Community level social capital in me of crisis
Fiji
Ghana
Sri Lanka
Vietnam
Fig 6 Correlation between social capital in time of crisis and resilience index
across the eight communities The straight line represents the linear relation
(R 2 = 077 F = 0004) and the bars are 95 con1047297dence intervals for each community
Random-effects parameters St Dev Std Err [95 Conf Interval]
country level
index_incom 043 024 0146 1266
index_livelih 051 027 0175 1464
index_housing 013 013 0018 0962
index_soc 039 024 0119 1303
index_soc_cris
078
038
0300
2009index_educ 015 013 0028 0834
const 090 067 0209 3861
community level
const 032 026 0066 1534
residuals 277 008 2617 2923
LR test vs linear regression chi2(7) = 3916 Prob gt chi2= 0000
p
lt 5
p
lt
1 p lt 1ma Fitting a three level model requires two random-effect equations one for level three (country) and one for level two (community) with i = 1 nvc 1047297rst level of
observation
(households)
nested
within
k
=
1
8
second
level
cluster
(community)
nested
within
j
=
1
4
third
level
cluster
(country)b The likelihood-ratio (LR) test comparing the nested mixed-effects model with the corresponding 1047297xed effect model con1047297rms the appropriate use of the mixed effect
model (chi2(7) = 3916 Prob gt chi2= 0000) and the Wald test con1047297rms that the independent variables are valid predictors (Wald chi2(45) = 59414 Prob gt chi2= 0000) A
speci1047297cation test performed on the 1047297xed effect model using a Pregibonrsquos goodness-of-link test shows good results (t = 077 P gt |t| = 0439)
c The dummy variables sev_event3 cat_event2 predict2 and comm_recov3 were omitted from the 1047297xed effect component for estimation purpose
Table 7 (Continued)
164 C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
The second potential limitation in our methodology relates to
the way the level of resilience of the households was assessed
While psychometric measurements are reliable and their results
replicable and testable when correctly implemented (Vigderhous
1977) one could fear that their use in the speci1047297c case of resilience
measurement could be subject to the effect of adaptive preference
that is the deliberate or re1047298exive process by which people adjust
their expectations and aspirations when trying to cope with
deterioration in living conditions (see eg Nussbaum 2001 Teschl
and Comim 2005) In our case this means that households
undergoing a degree of adaptive preference could have over-
estimated their ability to recover Although this risk is present we
tried to mitigate (or to reduce) it by introducing a qualifying
element in each of the coded answers of the resilience question-
naire so that respondents would have to associate the
1047297rst part of
their answer ldquoI have fully recoveredrdquo with a particular lsquoframe of
reference or quali1047297er (eg ldquoand it was not too dif 1047297cultrdquo) This frame
determined how they comprehend the questions being asked and
reduced the risk of the respondent simply relying on emotional
elements to answer these questions
Keeping in mind these potential limitations we now turn to
what we consider the most notable results of this research First is
the
lsquocumulative and continuous effect of shocks and stressors
whereby the impacts and disturbance of sequential shocksstressors and trends during the last 1047297ve years combine and
coalesce to create a constant non-stop stress We saw that the
nature and the source of events that were identi1047297ed by the
respondents in the four countries are all highly varied and
composite and reveal no speci1047297c clear pattern The events are a
combination of idiosyncratic and covariant sudden shocks and
long-term continuous trends Some are predictable while others
are totally unexpected All affect households simultaneously and
on an almost continuous basis The data suggests in particular that
on average households are hit by a new event every 16 months
This result calls into questions the framework generally used to
conduct shock or vulnerability assessment Often the approach has
been to disaggregate the problems people face and focus on single
threats such as eg 1047298ood or increase in food prices in order todevelop a clearer understanding of the impact of these particular
shocks and the ways people respond to them This approach has
been challenged however by a growing number of scholars who
argue that the reality households face on a daily basis is not linear
and mono-dimensional (OrsquoBrien and Leichenko 2000 Eriksen and
Silva 2009 Quinn et al 2011 McGregor 2011) Instead they argue
risks and vulnerability are often the product of multiple stressors
(Turner et al 2003 OrsquoBrien et al 2009) where social economic
political and biophysical factors interact combine and reinforce
each other to create a complex and dynamic multi-stressor multi-
shock environment (Reid and Vogel 2006 Adger 2006) Our
results corroborate this new interpretation
In line with this our analysis also shows that most households
engage in a suite of responses to a given shock On average
households adopted more than 4 types of responses to a particular
event This last result does not simply imply a rethinking of the way
shock or vulnerability assessments are conceptualized and
conducted see eg Turner et al (2003) or Leichenko and OrsquoBrien
(2008) It also demonstrates that the mental model (shock
gt response gt recovery) which is widely accepted in the
resilience literature is too simplistic and possibly misleading in
the sense that a state of (full) recovery may not exist This is at least
what was observed for the households included in our research
these households did not seem to have the chance or the time to
fully recover from one particular event before being affected by the
next Instead they were caught in what we could characterize as ldquoaconstant state of incomplete recoveringrdquo from new shocks and
stressors as illustrated in Fig 7
The next entry point in this discussion is wealth Our mixed
effect model (Table 7) shows that wealth was positively correlated
with household resilience Wealth has been identi1047297ed in the
literature as a key factor in strengthening the resilience of
households (Prowse and Scott 2008 WFP 2013) Analysis of
rural Ethiopian households hit by drought for instance showed that
while better-off households could sell livestock to smooth
consumption the poorer often tried to hold on to their livestock
at the expense of food consumption to preserve their options for
rebuilding herds The same study also shows that in the aftermath
of the hurricane Mitch in Honduras the relatively wealthy
households were able to rebuild their lost assets faster than thepoorest households for whom the effects of the hurricane were of
longer duration and felt much more acutely (Carter et al 2007) In
Fig 7 Left Current conceptualisation of resilience shock gt response gt recovery as presented in the literature [here redrawn from Carter et al 2007] Right actual
situation where the multi-stressor multi-shock environment induces that households are in a trajectory of continual and incomplete recovery Not represented here are the
multi-response
strategies
put
in
place
by
households
to
respond
to
these
adverse
events
C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170 165
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
disaster resilience National Disaster Resilience Roundtable Report 20September 2012 Melbourne Australia 36 p
Adger NW Dessai S Goulden M Hulme M Lorenzoni I Nelson DR Naess LO Wolf J Wreford A 2009 Are there social limits to adaptation to climatechange
Clim
Change
93
335ndash354Adger WN 2003 Social capital collective action and adaptation to climate
change Econ Geogr 79 (4) 387ndash404Adger WN 2006 Vulnerability Glob Environ Change 16 268ndash281Aldrich D 2010 Fixing recovery social capital in post-Crisis resilience J Homeland
Secur 6 1ndash10Ayers
J
Forsyth
T
2009
Community-based
adaptation
to
climate
changestrengthening resilience through development Environment 51 23ndash31
Beacuteneacute C Tew1047297k A 2001 Fishing effort allocation and 1047297shermenrsquos decision-makingprocess in a multi-species small-scale 1047297shery analysis of the conch and lobster1047297shery in Turks and Caicos Islands Hum Ecol 29 (2) 157ndash186
Beacuteneacute
C
Evans
L
Mills
D
Ovie
S
Raji
A
Ta1047297da
A
Kodio
A
Sinaba
F
Morand
PLemoalle J Andrew N 2011 Testing resilience thinking in a poverty contextexperience from the Niger river basin Glob Environ Change 21 (4) 1173ndash1184
Beacuteneacute C Godfrey-Wood R Newsham A Davies M2012 Resilience new utopia ornew tyranny
ndash Re1047298ection about the potentials and limits of the concept of
resilience
in
relation
to
vulnerability
reduction
programmes
IDS
Working
Paperno 405 Institute of Development Studies Brighton 61 p
Beacuteneacute C Newsham A Davies M Ulrichs M Godfrey-Wood R 2014 Resiliencepoverty and development J Int Dev 26 598ndash623
Beacuteneacute C Waid J Jackson-deGraffenried M Begum A Chowdhury M Skarin VRahman A Islam N Mamnun N Mainuddin K Shah MA 2015a Impact of climate-related
shocks
and
stresses
on
nutrition
and
food
security
in
ruralBangladesh Dhaka World Food Programme 119 p
Beacuteneacute C Frankenberger T Nelson S 2015b Design monitoring and evaluation of resilience interventions conceptual and empirical considerations IDS WorkingPaper no459 Institute of Development Studies 23 p
Beacuteneacute
C
2013
Towards
a
quanti1047297able
measure
of
resilience
IDS
Working
Paper
434Institute of Development Studies Brighton 27 p
Bandura A 1977 Self-ef 1047297cacy toward a unifying theory of behavioral changePsychol Rev 84 191ndash215
Baulch R Hoddinott J 2000 Economic mobility and poverty dynamics indeveloping countries J Dev Stud 36 (6) 1ndash23
Belhabib
D
Sumaila
UR
Pauly
D
2015
Feeding
the
poor
contribution
of
WestAfrican 1047297sheries to employment and food security Ocean Coast Manage 11172ndash81
Berkes F Folke C 1998 Linking social and ecological systems for resilience andsustainability In Berkes F Folke C (Eds) Linking Social and EcologicalSystems Management Practices and Social Mechanisms for Building ResilienceCambridge University Press Cambridge pp 1ndash25
Bernier Q Meinzen-Dick R 2014 Resilience and social capital Building Resiliencefor Food and Nutrition Security Conference Paper No 4 International FoodPolicy Research Institute Washington DC 26 p
Bhattamishra R Barrett C 2010 Community-Based risk managementarrangements a review World Dev 38 (7) 923ndash932
Boarini R Kolev A McGregor JA 2014 Measuring well-being and progress incountries at different stages of development towards a more universalconceptual framework OECD Working Paper No 235 Organisation forEconomic Co-operation and Development Development Center
ndash Better Life
Initiative Paris 59 p
Boyd E Osbahr H Ericksen P Tompkins E Carmen Lemos M Miller F 2008Resilience and
lsquoclimatizingrsquo development examples and policy implicationsDevelopment 51 390ndash396
Cam1047297eld
L
McGregor
JA
2005
Resilience
and
wellbeing
in
developing
countriesIn Ungar M (Ed) Handbook for Working with Children and Youth Pathwaysto Resilience Across Cultures and Contexts Sage Publications Thousand OaksCA
Cam1047297eld
L
Ruta
D
2007
Translation
is
not
enough
using
the
Global
PersonGenerated Index (GPGI) to assess individual quality of life in BangladeshThailand and Ethiopia Qual Life 16 (6) 1039ndash1051
Carter M Little P Mogues T Negatu W 2007 Poverty traps and natural disastersin Ethiopia and Honduras World Dev 35 (5) 835ndash856
Cleaver
F
2005
The
inequality
of
social
capital
and
the
reproduction
of
chronicpoverty World Dev 33 (6) 893ndash906
Constas M Frankenberger T Hoddinott J 2014a Resilience measurementprinciples toward an agenda for measurement design Resilience MeasurementTechnical Working Group Technical Series No 1 Food Security informationNetwork Rome
Constas MT Frankenberger J Hoddinott N Mock D Romano C Beacuteneacute DMaxwell 2014b A common analytical model for resilience measurementcausal framework and methodological options Food Security InformationNetwork (FSIN) Technical Series No 2 World Food Programme Rome
Coulthard S 2011 More than just access to 1047297sh the pros and cons of 1047297sherparticipation
in
a
customary
marine
tenure
(Padu)
system
under
pressure
MarPolicy 35 405ndash412
DFID 2011 De1047297ning Disaster Resilience A DFID Approach Paper Department forInternational Development London pp 20
Dercon S Hoddinott J Woldehanna T 2005 Shocks and consumption in 15ethiopian
villages
1999ndash2004
J
Afr
Econ
14
(4)
559ndash585Dercon S 1996 Risk crop choice and savings evidence from Tanzania Econ Dev
Cult Change 44 (3) 485ndash513Duit A Galaz V Eckerberg K 2010 Governance complexity and resilience Glob
Environ Change 20 (3) 363ndash368Eriksen
SEH
Silva
JA
2009
The
vulnerability
context
of
a
savannah
area
inMozambique household drought coping strategies and responses to economicchange Environ Sci Policy 12 (1) 33ndash52
Fafchamps M Lund S 2003 Risk-Sharing networks in rural Philippines J DevEcon 71 (2) 261ndash287
Frankenberger T Nelson S 2013 Background Paper for the Expert Consultation onResilience
Measurement
for
Food
Security
TANGO
International
Rome
Foodand Agricultural Organization and World Food Program
Heltberg R Siegel PS Jorgensen SL 2009 Addressing human vulnerability toclimate change towards a
lsquono-regretsrsquo approach Glob Environ Change 19 89ndash99
Hoddinott
J
Dercon
S
Krishnan
P
2009
Networks
and
informal
mutual
supportin 15 ethiopian villages a description In Kirsten JF Dorward AR Poulton CVink N (Eds) Institutional Economics Perspectives on African AgriculturalDevelopment International Food Policy Research Institute Washington DC pp273ndash286
Hoddinott
J
2006
Shocks
and
their
consequences
across
and
within
households
inRural Zimbabwe J Dev Stud 42 (2) 301ndash321
Intergovernmental Panel on Climate Change (IPCC) 2012 In Field CB Barros VStocker TF Qin D Dokken DJ Ebi KL Mastrandrea MD Mach KJPlattner G-K Allen SK Tignor MMidgley PM (Eds) Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation A SpecialReport of Working Groups I and II of the Intergovernmental Panel on ClimateChange Cambridge University Press Cambridge UK
Jackson T 2005 Motivating sustainable consumptionmdasha review of evidence onconsumer behaviour and behavioural change A Report to the Sustainable
Event type (Vietnam) Reduce
expenditures
Borrow
money
Reduce
Food
Change
1047297shing
strategy
Get
support
Increase
1047297shing
effort
Diversi1047297cation Seek new
collaboration
Migration Exit the
1047297shery
Sell
assets
Total
Others (aggregated) 4 7 4 6 3 0 1 3 0 0 2 30
Erosion 2 4 2 1 6 2 2 2 3 1 25
Catch reduced
suddenly
8 4 6 7 1 2 4 2 34
Gears lost 10 18 6 5 1 2 1 43
Cold wind prolongs 15 7 11 3 1 7 2 46
Typhoon
12
11
10
2
4
2
3
5
4
1
1
55
Illness
11 14
6
2
11
2
2
4
1
1
2
56Food price increase 20 17 19 2 8 5 1 72
Input price increase
continuously
47 39 33 21 40 5 6 16 1 208
Big boats compete
ground and catch
54 39 32 40 9 19 11 15 8 3 2 232
Catch
reduced
continuously
102
70
80
63
22
51
51
25
23
17
6
510
Total 285 230 209 152 105 91 87 75 39 23 15 1311
C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170 169
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
Development Research Network Centre for Environmental StrategiesUniversity of Surrey
Jones L Boyd E 2011 Exploring social barriers to adaptation insights fromWestern Nepal Glob Environ Change 21 (4) 1262ndash1274
Kallstrom HN Ljung M 2005 Social sustainability and collaborative learningAmbio 34 376ndash382
Kelty R Kelty R 2011 Human dimensions of a 1047297shery at a crossroads resourcevaluation identity and way of life in a seasonal 1047297shing community Soc NatResour
24
(4)
334ndash348Klein RJT Nicholls RJ Thomalla F 2003 Resilience to natural hazards how
useful is this concept Environ Hazards 5 35ndash45
Krosnick
JA
Fabrigar
LR
1997
Designing
rating
scales
for
effective
measurementin surveys In Lyberg L Biemer P Collins M de Leeuw E Dippo C SchwarzN
Trewin
D
(Eds)
Survey
Measurement
and
Process
Quality
John
Wiley
andSons Inc New York NY pp 141ndash164
Leichenko R OrsquoBrien K 2008 Environmental Change and Globalization DoubleExposures Oxford University Press New York
Marschke M Berkes F 2006 Exploring Strategies that build livelihood resiliencea case from Cambodia Ecol Soc 11 (1) httpwwwecologyandsocietyorgvol11iss1art42
McGregor JA Cam1047297eld L Woodcock A 2009 Needs wants and goals wellbeingquality
of
life
and
public
policy
Appl
Res
Qual
Life
4
135ndash154McGregor JA 1994 Village credit and the reproduction of poverty in rural
Bangladesh In Acheson J (Ed) Economic Anthropology and the NewInstitutional Economics University Press of AmericaSociety for EconomicAnthropology Washington pp 261ndash281 (Chapter)
McGregor
JA
2011
Reimagining
development
through
the
crisis
watch
initiative
IDS Bull 42 (5) 17ndash23McLaughlin P Dietz T 2007 Structureagency and environment toward an
integrated perspective on vulnerability Glob Environ Change 39 (4) 99ndash111Meyer MA 2013 Social capital and resilience in the context of disaster social
capital
and
collective
ef 1047297cacy
for
disaster
resilience
connecting
individualswith communities and vulnerability with resilience in hurricane-pronecommunities in Florida PhD Dissertation Department of sociology Coloradostate University Fort Collins Colorado (311 p)
Mills DJ Adhuri D Phillips M Ravikumar B Padiyar AP 2011 Shocks recoverytrajectories and resilience among aquaculture-dependent households in post-tsunami
Aceh
Indonesia
Local
Environ
Int
J
Justice
Sustain
16
(5)
425ndash444Morduch J 1995 Income smoothing and consumption smoothing J Econ
Perspect 9 (3) 103ndash114Morris S Carletto C Hoddinott J Christiaensen L 2000 J Epidemiol Commun
Health 54 381ndash387Myers
RA
Worm
B
2003
Rapid
worldwide
depletion
of
predatory 1047297sh
communities Nature 423 280ndash283Nakagawa Y Shaw R 2004 Social capital a missing link to disaster recovery Int J
Mass
Emerg
Disasters
22
(1)
5ndash
34Nussbaum MC 2001 Adaptive preferences and womenrsquos options Econ Philos 1767ndash88
Oslashstergaard N Reenberg A 2010 Cultural barriers to climate change adaptation acase study from Northern Burkina Faso Glob Environ Change 20 (1) 142ndash152
OrsquoBrien K Leichenko R 2000 Double exposure assessing the impacts of climatechange within the context of economic globalization Glob Environ Change 10221ndash232
OrsquoBrien K Eriksen S Sygna L Naess LO 2006 Questioning complacencyclimate change impacts vulnerability and adaptation in Norway AMBIO JHum Environ 35 (2) 50ndash56
OrsquoBrien K Quilan T Ziervogel G 2009 Vulnerability interventions in the contextof multiple stressors lessons from the Southern Africa vulnerability initiative(SAVI) Environ Sci Policy 12 23ndash32
OrsquoRiordan T Jordan A 1999 Institutions climate change and cultural theorytowards a common analytical framework Glob Environ Change 9 (2) 81ndash93
Pain A Levine S 2012 A conceptual analysis of livelihoods and resilienceaddressing the
lsquoinsecurity of agency HPG Working Paper OverseasDevelopment Institute Humanitarian Policy Group London
Pauly D Christensen V Dalsgaard Froese JR Torres F 1998 Fishing downmarine food webs Science 279 (5352) 860ndash863
Pelling M Manuel-Navarrete D 2011 From resilience to transformation theadaptive cycle in two Mexican urban centersEcol Soc 16 (2)11 (online) httpwwwecologyandsocietyorgvol16iss2art11
Prowse
M
Scott
L
2008
Assets
and
adaptation
an
emerging
debate
IDS
Bull
39(4) 42ndash52
Putzel J 1997 Accounting for the lsquodark sidersquo of social capital reading Robert
Putnam
on
democracy
J
Int
Dev
9
(7)
939ndash949
Quinn CH Ziervogel G Taylor A Takama T Thomalla F 2011 Coping withmultiple
stresses
in
rural
South
Africa
Ecol
Soc
16
(3)
doihttpdxdoiorg105751ES-04216-160302
Reid P Vogel C 2006 Living and responding to multiple stressors in South Africamdashglimpses from KwaZulu-Natal Glob Environ Change 16 (2) 195ndash206
Roncoli C Ingram K Kirshen P 2001 The costs and risks of coping with droughtlivelihood
impacts
and
farmersrsquo
responses
in
Burkina
Faso
Clim
Res
19
119ndash132
Schwarz AM Beacuteneacute C Bennett G Boso D Hilly Z Paul C Posala R Sibiti SAndrew N 2011 Vulnerability and resilience of rural remote communities toshocks and global changes empirical analysis from the Solomon Islands GlobEnviron Change 21 1128ndash1140
Sinha
S
Lipton
M
Yaqub
S
2002
Poverty
and
damaging 1047298uctuations
how
dothey relate J Asian Afr Stud 37 (2) 186ndash243
Tansey J OrsquoRiordan T 1999 Cultural theory and risk a review Health Risk Soc 171ndash90
Teschl M Comim F 2005 Adaptive preferences and capabilities somepreliminary
conceptual
explorations
Rev
Soc
Econ
63
(2)
229ndash247
Trimble M Johnson D 2013 Artisanal 1047297shing as an undesirable way of life Theimplications for governance of 1047297shersrsquo wellbeing aspirations in coastal Uruguayand southeastern Brazil Mar Policy 37 37ndash44
Turner BL Kasperson RE Matson P McCarthy JJ Corell RW Christensen LEckley
N
Kasperson
JX
Luers
A
Martello
ML
Polsky
C
Pulsipher
ASchiller A 2003 A framework for vulnerability analysis in sustainabilityscience Proc Natl Acad Sci 100 (14) 8074ndash8079
Vigderhous G 1977 The level of measurement and
lsquoPermissiblersquo statistical analysisin social research Pac Sociol Rev 20 (1) 61ndash72
WFP 2013 Building Resilience Through Asset Creation Resilience and PreventionUnit
Policy
Programme
and
Innovation
Division
World
Food
Program
Rome(23 p)
Walker B Carpenter S Anderies J Abel N Cumming GS Janssen M Lebel LN J Peterson GD Pritchard R 2002 Resilience management in social-ecological systems a working hypothesis for a participatory approach ConservEcol
6
(1)
14Weber EU 2010 What shapes perceptions of climate change Clim Change 1 (3)
332ndash342
Wolf
J
Adger
WN
Lorenzoni
I
Abrahamson
V
Raine
R
2010
Social
capitalindividual responses to heat waves and climate change adaptation an empiricalstudy
of
two
UK
cities
Glob
Environ
Change
20
44ndash52Wood G 2003 Staying secure staying poor the Faustian bargain World Dev 31
(3) 455ndash471World Bank 2011 Building Resilience and Opportunities World Bankrsquos Social
Protection and Labour Strategy 2012ndash2022 World Bank Washington DCYamano T Alderman H Christiaensen L 2003 Child Growth Shocks and Food
Aid in Rural Ethiopia World Bank Washington DCZimmerman F Carter M 2003 Asset smoothing consumption smoothing and the
reproduction of inequality under risk and subsistence constraints J Dev Econ71 233ndash260
von Grebmer K Headey D Beacuteneacute C Haddad L et al 2013 Global Hunger IndexThe Challenge of Hunger Building Resilience to Achieve Food and NutritionSecurity Welthungerhilfe International Food Policy Research Institute andConcern Worldwide Bonn Washington DC and Dublin
170 C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
when all events are aggregated households are hit by a new event
of some kind every 485 days that is every 16 months
42 Household response analysis
The next step was to document and analyse the various types of
strategies that households employed in the face of shocks and
stressors In the resilience analysis framework (Fig 1) this
corresponds to the
lsquoresponse analysisrsquo component
Fig 4 presents the event-response matrices for the four country
case studies (computed for the ten most cited events per country)
The colour codes correspond to the four categories described in
Table 1 coping strategies social-relation based strategies 1047297shery-
related strategies and non-1047297shery-related strategies
The matrices show that coping strategies are the most frequent
responses put in place by households Amongst coping strategies
reduction of food consumption and reduction of general expenses
were commonly adopted while asset selling was notable for being
seldom adopted except in Ghana Beyond the generic pattern of
0 005 01 015 02 025 03 035
Others
High de
Destruconlossthe of fishing gear
Sudden change in sea condion
Slow increase in input prices
Major health problem
Death
Flood
Rapid (peak) increase in input prices
Decline in fish price
Sudden decli ne in catch
Slow decline in catch
Slow increase in food prices
Important change in fishing techniques
Any other fishery rela ted issue
unpredictable c hanges in weather
Hurricane
Percentage (total = 100)
Fiji
ST
MT
LT
0 005 01 015 02 025 03
Others
Increase in Food Price
Storm and strong winds
Unpred weather change
Accident Disability
Change in sea condion
Loss of financial assets
Loss of other assetsLoss fishing ground
Flood
Fish price increase
Sick family member
Death of family member
Destrucon The Loss gear
Input prices increase
Change in fishing techniques
Fuel shortage
Slow decline in catch
Percentage (total = 100)
Ghana
ST
MT
LT
0 005 01 015 0
Others
Slow but constant increase in input prices
Death of a family m ember
Other major weather event
Sudden change in sea condion
Flood
Sudden decline in catch
Loss of other assets other than fishing gear
Major health problem (sickness)
Decline in fish price
More unpredictable changes in weather paern
Important change in fishing techniquesSlow decline in catch
Limitaons-Harbour
New constraining fishing regulaon
Destruconlossthe of fishing gear
Rapid (peak) increase in input prices
Hurricane tropical storm
Perccentage (total = 100)
Sri Lanka
ST
MT
LT
0
005
01
015
02
025
03
035
04
045
Others
Lost assets
Accident
Erosion
Catch r educed suddently
Gears lost
Cold wind prolongs
Typhoon
Illness
Food price increase
Input price increa se connuously
Big boats compete ground and catch
Catch reduced connuously
Percentage (total = 100)
Vietnam
ST
MT
LT
Fig 2 Adverse event inventory for the four countries Events have been grouped and colour-coded into three categories short and unpredictable shocks (ST) (ii) medium-
term stressors that last several months andor are recurrent (MT) and (iii) long-term trends (LT)
0 10 20 30
Annually
On a connuous (daily) basis
Every 5 years
Bi-annually
Quarterly basis
Weekly basis
Monthly basis
Every two-year
Every 10 years
Every 20 year or less oen
Percentage of responses (total = 100)
(c) Event frequency
0
10
20
30
40
50
60
70
1 2 3 4 5
P e r c e n t a g e o f r e s p o n s e s ( t o t a l = 1 0 0 )
5-point scale rang
(b) Event severity
very bad lt ---------------------------------- gt posive
0
10
20
30
40
1 2 3 4 5
P e r c e n t a g e o f r e s p o n s e s ( t o t a l = 1 0 0 )
Fig 4 Event-response matrices for the four country case studies The numbers in the column are percentage of total responses ranked from the most (left) to the least (right)
adopted
and
colour-coded
using
the
typology
presented
in
Table
1 Full
details
are
provided
in
Appendix
A
Table 4
Average number of responses per event at the community level
Country Community Mean Std Err [95 Conf Interval]
Fiji A 27 022 232 317
B 26 007 244 272
Ghana C 43 018 389 461
D 39 016 359 421
Sri
Lanka
E
55
020
514
594F 76 026 707 809
Vietnam G 34 012 319 367
H 35 019 308 383
Total
(N
=
1868)
46
005
451
474
C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170 159
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
Resilience outcomes were explored using psychometric tech-
niques where households were asked to self-assess the degree of
recovery they managed to achieve for each of the adverse events
they had experienced in the past (see details in Table 2) The
answers provided by the respondents to the 1047297rst two questions of
the resilience analysis (self-recovery from past event and self-
recovery compared to the rest of the community) were used to
create a resilience index (RI) computed as the product of the two
scores As a result of the calculation process RI is an integer varying
between 1 and 30 where low values indicate low level of resilienceto a speci1047297c event while higher values indicate higher levels of
resilience
We then used this resilience index to explore the last remaining
working hypothesis of this research that is that
lsquosocial capital is
importantrsquo- ie the (intuitive) idea that households or communi-
ties characterized by higher level of social capital are able to draw
on social capital to help themselves (and others) in the aftermath
of an adverse event To analyse the resilience outcomes and explore
in particular this last hypothesis a three-level mixed effect linear
model was run where the resilience index was tested against a
series of 1047297xed and random factors used as independent explana-
tory variables Because the communities are nested within the
countries a three-level (hierarchical) model was
1047297tted with
random intercepts at both country and community-within-
country levels Random coef 1047297cients were also accounted for at
the country level on the Quality of Life (QoL) factors to re1047298ect
country speci1047297c effects More speci1047297cally the model was of the
form
RI vc frac14 b0 thorn b1Shockvc thorn b2Respvc thorn b3QoLvc thorn b4HH vc thorn g 1W c thorn g 2 Z vc thorn
evc
where the subscripts v and c hold for village (community) and
country respectively Shockvc is the covariate matrix for the
1047297xed
effect
b1 of the impacts of event e on individual household Respvc
is the covariate matrix for the 1047297xed effect b2 of the responses put in
places by the household QoLe is the covariate matrix for the
1047297xed
effect b3 of the Quality of Life scores recorded for each household
HH e is the matrix of variables and dummies controlling for
household characteristics W c is the covariate matrix for the cluster
random effect at the country level and Z vc is the covariate matrix
for the cluster random effect at the community level The details of
the different categories of variables included in the model are
provided in Table 6
Results of the model estimations including details of both
1047297xed and random effect speci1047297cations and diagnostic checking-
are presented in Table 7 The model highlights a series of important
1047297ndings First the degree of severity of the shock and the
disruptive impact on income are the twoshock variables that have
0
10
20
30
40
50
60
70
80
90
F o o d
E x p e n s e s
M o n e y
A s s e s t
S u p p o r t
C o l l a b o r a o n
D i v e r s i fi c a o n
M i g r a o n
E x i t
C h a n g e
I n c r e a s e
P e r c e n t a g e o f h o u s e h o l d s ( )
Response typology (Vietnam)
Boom 40
Top 40
0
01
02
03
04
05
06
07
F o o d
E x p e n s e s
M o n e y
A s s e t s
S u p p o r t
C o l l a b o r a o n
D i v e r s i fi c a o n
M i g r a o n
E x i t
C h a n g e
I n c r e a s e
P e r c e n t a g e o f h o u s e h o l d s ( )
Response typology (Fiji)Boom 40
Top 40
Fig 5 Comparative analysis of the responses adopted by the bottom (poorest) and top (wealthiest) 40 of the households when affected by the same event illustration
from Vietnam and Fiji Code of the responses
ldquoFoodrdquo = Reduce food consumption
ldquoExpensesrdquo = Reduce family general expenses
ldquoMoneyrdquo = Borrow money
ldquoAssetsrdquo = Sell
family assets
ldquoSupportrdquo= Seek for support from friends and peers
ldquoCollaborationrdquo= Develop new collaboration within the community
ldquoDiversi1047297cationrdquo = Invest in non-
1047297shery activities ldquoMigrationrdquo = Temporary permanently migration one or several members of the family ldquoExitrdquo = Exit the 1047297shery start a new joblivelihoodldquoChangerdquo = Change 1047297shing strategies
ldquoIncreaserdquo = Increase 1047297shing effort
160 C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
The type of responses adopted by households was included in
the model to test whether the level of resilience of households is
effectively in1047298uenced by those responses Amongst the 11 types of
responses tested three have statistically signi1047297cant signs engag-
ing
in
new
collaboration
(negative
sign
P
=
0001)
increasing1047297shing effort (positive P lt 00001) and quitting the
1047297shery
(negative P = 0047) The negative correlation found between
household resilience and the strategy that consists of forming new
collaboration may be dif 1047297cult to interpret as it can re1047298ect many
highly contextual factors The two others responses and the signs
of their correlations (one negative sign for leaving the sector and
one positive sign for increasing 1047297shing effort) are initially
disturbing but eventually not too surprising Disturbing
1047297rst
because this
1047297nding does not lead to the type of long-term
behaviours that appeal to policy makers and 1047297shery managers On
the contrary they would rather see 1047297shing effort reductions and
exit strategies more often adopted by
1047297shers in particular in the
context of the current world
1047297shery crisis Not surprising however
because this result is in line with what one could expect from
1047297sherfolks after an adverse event in the face of a long-term stress
(such
as
the
drop
in
income
following
a
continuous
decline
in
1047297shcatch) or a sudden need for cashrevenues (as a consequence of
eg destruction of 1047297shing gear induced by bad weather or the
need to pay health bills)
1047297shers are often observed to alter their
1047297shing activities to make up for these events usually by changing
adjusting their 1047297shing strategy (eg switching between targeted
species andor
1047297shing gear) or increasing their
1047297shing effort (eg
investing in more ef 1047297cient
1047297shing gear increasing the quantity of
gear used or increasing the number of days at sea) in an attempt to
generate more cash In that context it is not surprising that the
majority of 1047297shing households interviewed in this research
consider that their ability to
lsquobounce back following an adverse
event was enhanced when they increase their 1047297shing effort
Additionally given what we know about their strong sense of
identity
(Kelty
and
Kelty
2011
Trimble
and
Johnson
2013) but
alsothe importance of peer-pressure and reputation (see eg Beacuteneacute and
Tew1047297k 2001) quitting the 1047297shery would certainly be perceived by
many 1047297shers as a failure thus the negative correlation between
(perceived) resilience and leaving the sector
The next category of variables which was investigated through
the model was the Quality of Life indicators (see Table 3 for a
recall) A reasonable hypothesis although not explicitly formu-
lated in the
lsquoworking hypotheses section above- is that some of
these QoL indices may have a positive effect on the ability of
households to handle and recover from adverse events One can
indeed assume that households satis1047297ed in many of the
dimensions of wellbeing which they considers important (such
as say access to health services or to public infrastructure) may
feel better equipped to reactrespond to any particular event than
Table 5
Top comparison of propensities to adopt particular types of responses for households characterized by high (N = 224) and low (N = 235) subjective resilience Bottom
comparison of the two same groups in terms of asset levels education and age of the household head
Responses subjective
resilience
level
Mean [95 Conf
Interval]
test resulta
Coping strategies High 198 1840 2136 t = 43037 Pr(|T| gt |
t|) = 0000
Low 245 2311 2596
Social-relation-based strategies High 083 0738 0927 t = 05187 Pr(|T| gt |
t|) = 0604
Low 086 0787 0943
Fishing-related strategies High 083 0732 0935 t = 03267 Pr(|T| gt |
t|)
=
0744
Low 081 0715 0906
Non-1047297shery
strategies
High
067
0559
0794
t
=
35599
Pr(|T|
gt
|
t|) = 0000
Low 042 0341 0502
Household characteristics
Asset High 768 7218 8157 t = 08882 Pr(|T| gt |
t|) = 0374
Low 739 6938 7848
Education High 796 7338 8599 t = 10186 Pr(|T| gt |
t|)
=
0308
Low 750 6857 8147
Age High 4688 45377 48391 t = 01332 Pr(|T| gt |
t|) = 0894
Low 4702 45570 48482
p
lt 5
p
lt 1
p
lt 1
a mean difference unpaired t -test Ho Diff = 0 Ha diff 6frac14 0
C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170 161
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
diversif non 1047297sher diversi1047297cation dummy 1 = yes
exit_1047297sh exit the 1047297shery sector dummy 1 = yes
migrat migrate dummy 1 = yes
quality of life indices
index_incom
income
index
ordinal
variable
coded
[-6
+6]
ndash6
=
very
poor
+6
=
very
strong
index_livelih livelihood index ordinal variable coded [-6 +6] ndash6 = very poor +6 = very strongindex_housing housing and infrastructure index ordinal variable coded [-6 +6] ndash6 = very poor +6 = very strong
index_educ education index ordinal variable coded [-6 +6]
ndash6 = very poor +6 = very strong
index_soc social capital index ordinal variable coded [-6 +6]
ndash6 = very poor +6 = very strong
index_health health index ordinal variable coded [-6 +6] ndash6 = very poor +6 = very strong
ind_emp empowerment index ordinal variable coded [-6 +6]
ndash6 = very poor +6 = very strong
index_soc_cris social capital index in time of crisis
ndash6 = very poor +6 = very strong
index_emp_cris empowerment index in time of crisis
ndash6 = very poor +6 = very strong
index_spirit index of spirituality
ordinal variable coded [-6 +6]
ndash6 = very poor +6 = very strong
household characteristics
HH head sex sex of household head dummy 1 = female
HH
head
age
age
of
household
head
age
in
years
HH head educ level of education of the household head 0 = no education 20 = post-graduate level
HH size size of household number of members (not adjusted for age)
log_asset household assets (log-transformed) value of household assets (proxy for wealth level)
community
resiliencecomm_recov level of recovery of the community
a Fitting a three level model requires two random-effect equations one for level three (country) and one for level two (community) with i = 1 nvc 1047297rst level of
observation (households) nested within k = 1 8 s level cluster (community) nested within j = 1 4 third level cluster (country)
162 C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
community level in the same way than the QoL indices that is by
averaging the scores obtained at the individual household level)
The best correlation was obtained with the QoL index of social
capital in time of crisis (R 2= 077 F = 0004) see Fig 6- suggesting
that communities with higher social capital in time of crisis are
also characterized by higher level of resilience
5 Discussion
Resilience has been increasingly recognized as a potentially
useful concept to help practitioners academics and policy-makers
better understand the links between shocks response and longer-
term development outcomes (Constas et al 2014a Beacuteneacute et al
2014) Incorporating resilience alongside vulnerability analysis can
contribute an essential element to societal ability to better prepare
for future shocks and stressors This paper argues that improving
our understanding of what contributes to or constitutes peoplersquos
resilience requires not only the development and
1047297eld-testing of
robust and measurable indices (Beacuteneacute 2013 Constas et al 2014b)
but also a better insight into the social factors including
knowledge perceptions and motivations- that in1047298uence and affect
individual and collective capacity to respond to shocks and
stressors
Our analysis conducted in eight 1047297shery-dependent communi-
ties from Fiji Ghana Sri Lanka and Vietnam reveals a series of
notable results in relation to these questions In considering these
outcomes it is important to 1047297rst take stock of potential limitations
pitfalls or biases in the study methodology Given the nature of the
1047297ndings two potential issues require further consideration First is
the question of how representative our sampling methodology
was It could be argued for instance that the observed low adoption
rates of non-1047297shery strategiesndash and in particular the low score of
the
lsquoexiting the
1047297sheryrsquo was driven by our sampling method
underrepresenting these groups as those who had effectively left
the 1047297shery were not included in the sample
The FGDs that preceded the household survey speci1047297cally
addressed this issue In Sri Lanka for instance the opening question
prompted participants (both men and women) to discuss whether
ldquo1047297shers in their community had ever left 1047297sheries due to their
inability to cope with adverse eventsrdquo The answer was that it
generally does not happen with the notable exception of someyoung
1047297shers who attempted to migrate to Australia through
illegal means If it occurred exiting the 1047297shery was said to be
temporary ldquothey may leave the village or 1047297shing but will come
back when the situation is favourablerdquo In Vietnam the sampling
was speci1047297cally designed to cover both
1047297shers and ex-1047297shers in
proportions represented in the community As a result 9 ex-1047297shers
were included in the sample Overall therefore although we were
unable to conceive of a completely representative sampling design
(in the statistical sense) the parallel information that was collected
in the FGDs and the individual households converge to suggest that
exiting the
1047297shery was not an option envisaged by the members of
these different communities and consequently that our sampling
was not too severely biased
0
2
4
6
8
10
12
14
16
-05 05 15 25
C o m m u n i t y l e v e l r e s i l i
e n c e i n d e x
Community level social capital in me of crisis
Fiji
Ghana
Sri Lanka
Vietnam
Fig 6 Correlation between social capital in time of crisis and resilience index
across the eight communities The straight line represents the linear relation
(R 2 = 077 F = 0004) and the bars are 95 con1047297dence intervals for each community
Random-effects parameters St Dev Std Err [95 Conf Interval]
country level
index_incom 043 024 0146 1266
index_livelih 051 027 0175 1464
index_housing 013 013 0018 0962
index_soc 039 024 0119 1303
index_soc_cris
078
038
0300
2009index_educ 015 013 0028 0834
const 090 067 0209 3861
community level
const 032 026 0066 1534
residuals 277 008 2617 2923
LR test vs linear regression chi2(7) = 3916 Prob gt chi2= 0000
p
lt 5
p
lt
1 p lt 1ma Fitting a three level model requires two random-effect equations one for level three (country) and one for level two (community) with i = 1 nvc 1047297rst level of
observation
(households)
nested
within
k
=
1
8
second
level
cluster
(community)
nested
within
j
=
1
4
third
level
cluster
(country)b The likelihood-ratio (LR) test comparing the nested mixed-effects model with the corresponding 1047297xed effect model con1047297rms the appropriate use of the mixed effect
model (chi2(7) = 3916 Prob gt chi2= 0000) and the Wald test con1047297rms that the independent variables are valid predictors (Wald chi2(45) = 59414 Prob gt chi2= 0000) A
speci1047297cation test performed on the 1047297xed effect model using a Pregibonrsquos goodness-of-link test shows good results (t = 077 P gt |t| = 0439)
c The dummy variables sev_event3 cat_event2 predict2 and comm_recov3 were omitted from the 1047297xed effect component for estimation purpose
Table 7 (Continued)
164 C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
The second potential limitation in our methodology relates to
the way the level of resilience of the households was assessed
While psychometric measurements are reliable and their results
replicable and testable when correctly implemented (Vigderhous
1977) one could fear that their use in the speci1047297c case of resilience
measurement could be subject to the effect of adaptive preference
that is the deliberate or re1047298exive process by which people adjust
their expectations and aspirations when trying to cope with
deterioration in living conditions (see eg Nussbaum 2001 Teschl
and Comim 2005) In our case this means that households
undergoing a degree of adaptive preference could have over-
estimated their ability to recover Although this risk is present we
tried to mitigate (or to reduce) it by introducing a qualifying
element in each of the coded answers of the resilience question-
naire so that respondents would have to associate the
1047297rst part of
their answer ldquoI have fully recoveredrdquo with a particular lsquoframe of
reference or quali1047297er (eg ldquoand it was not too dif 1047297cultrdquo) This frame
determined how they comprehend the questions being asked and
reduced the risk of the respondent simply relying on emotional
elements to answer these questions
Keeping in mind these potential limitations we now turn to
what we consider the most notable results of this research First is
the
lsquocumulative and continuous effect of shocks and stressors
whereby the impacts and disturbance of sequential shocksstressors and trends during the last 1047297ve years combine and
coalesce to create a constant non-stop stress We saw that the
nature and the source of events that were identi1047297ed by the
respondents in the four countries are all highly varied and
composite and reveal no speci1047297c clear pattern The events are a
combination of idiosyncratic and covariant sudden shocks and
long-term continuous trends Some are predictable while others
are totally unexpected All affect households simultaneously and
on an almost continuous basis The data suggests in particular that
on average households are hit by a new event every 16 months
This result calls into questions the framework generally used to
conduct shock or vulnerability assessment Often the approach has
been to disaggregate the problems people face and focus on single
threats such as eg 1047298ood or increase in food prices in order todevelop a clearer understanding of the impact of these particular
shocks and the ways people respond to them This approach has
been challenged however by a growing number of scholars who
argue that the reality households face on a daily basis is not linear
and mono-dimensional (OrsquoBrien and Leichenko 2000 Eriksen and
Silva 2009 Quinn et al 2011 McGregor 2011) Instead they argue
risks and vulnerability are often the product of multiple stressors
(Turner et al 2003 OrsquoBrien et al 2009) where social economic
political and biophysical factors interact combine and reinforce
each other to create a complex and dynamic multi-stressor multi-
shock environment (Reid and Vogel 2006 Adger 2006) Our
results corroborate this new interpretation
In line with this our analysis also shows that most households
engage in a suite of responses to a given shock On average
households adopted more than 4 types of responses to a particular
event This last result does not simply imply a rethinking of the way
shock or vulnerability assessments are conceptualized and
conducted see eg Turner et al (2003) or Leichenko and OrsquoBrien
(2008) It also demonstrates that the mental model (shock
gt response gt recovery) which is widely accepted in the
resilience literature is too simplistic and possibly misleading in
the sense that a state of (full) recovery may not exist This is at least
what was observed for the households included in our research
these households did not seem to have the chance or the time to
fully recover from one particular event before being affected by the
next Instead they were caught in what we could characterize as ldquoaconstant state of incomplete recoveringrdquo from new shocks and
stressors as illustrated in Fig 7
The next entry point in this discussion is wealth Our mixed
effect model (Table 7) shows that wealth was positively correlated
with household resilience Wealth has been identi1047297ed in the
literature as a key factor in strengthening the resilience of
households (Prowse and Scott 2008 WFP 2013) Analysis of
rural Ethiopian households hit by drought for instance showed that
while better-off households could sell livestock to smooth
consumption the poorer often tried to hold on to their livestock
at the expense of food consumption to preserve their options for
rebuilding herds The same study also shows that in the aftermath
of the hurricane Mitch in Honduras the relatively wealthy
households were able to rebuild their lost assets faster than thepoorest households for whom the effects of the hurricane were of
longer duration and felt much more acutely (Carter et al 2007) In
Fig 7 Left Current conceptualisation of resilience shock gt response gt recovery as presented in the literature [here redrawn from Carter et al 2007] Right actual
situation where the multi-stressor multi-shock environment induces that households are in a trajectory of continual and incomplete recovery Not represented here are the
multi-response
strategies
put
in
place
by
households
to
respond
to
these
adverse
events
C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170 165
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
disaster resilience National Disaster Resilience Roundtable Report 20September 2012 Melbourne Australia 36 p
Adger NW Dessai S Goulden M Hulme M Lorenzoni I Nelson DR Naess LO Wolf J Wreford A 2009 Are there social limits to adaptation to climatechange
Clim
Change
93
335ndash354Adger WN 2003 Social capital collective action and adaptation to climate
change Econ Geogr 79 (4) 387ndash404Adger WN 2006 Vulnerability Glob Environ Change 16 268ndash281Aldrich D 2010 Fixing recovery social capital in post-Crisis resilience J Homeland
Secur 6 1ndash10Ayers
J
Forsyth
T
2009
Community-based
adaptation
to
climate
changestrengthening resilience through development Environment 51 23ndash31
Beacuteneacute C Tew1047297k A 2001 Fishing effort allocation and 1047297shermenrsquos decision-makingprocess in a multi-species small-scale 1047297shery analysis of the conch and lobster1047297shery in Turks and Caicos Islands Hum Ecol 29 (2) 157ndash186
Beacuteneacute
C
Evans
L
Mills
D
Ovie
S
Raji
A
Ta1047297da
A
Kodio
A
Sinaba
F
Morand
PLemoalle J Andrew N 2011 Testing resilience thinking in a poverty contextexperience from the Niger river basin Glob Environ Change 21 (4) 1173ndash1184
Beacuteneacute C Godfrey-Wood R Newsham A Davies M2012 Resilience new utopia ornew tyranny
ndash Re1047298ection about the potentials and limits of the concept of
resilience
in
relation
to
vulnerability
reduction
programmes
IDS
Working
Paperno 405 Institute of Development Studies Brighton 61 p
Beacuteneacute C Newsham A Davies M Ulrichs M Godfrey-Wood R 2014 Resiliencepoverty and development J Int Dev 26 598ndash623
Beacuteneacute C Waid J Jackson-deGraffenried M Begum A Chowdhury M Skarin VRahman A Islam N Mamnun N Mainuddin K Shah MA 2015a Impact of climate-related
shocks
and
stresses
on
nutrition
and
food
security
in
ruralBangladesh Dhaka World Food Programme 119 p
Beacuteneacute C Frankenberger T Nelson S 2015b Design monitoring and evaluation of resilience interventions conceptual and empirical considerations IDS WorkingPaper no459 Institute of Development Studies 23 p
Beacuteneacute
C
2013
Towards
a
quanti1047297able
measure
of
resilience
IDS
Working
Paper
434Institute of Development Studies Brighton 27 p
Bandura A 1977 Self-ef 1047297cacy toward a unifying theory of behavioral changePsychol Rev 84 191ndash215
Baulch R Hoddinott J 2000 Economic mobility and poverty dynamics indeveloping countries J Dev Stud 36 (6) 1ndash23
Belhabib
D
Sumaila
UR
Pauly
D
2015
Feeding
the
poor
contribution
of
WestAfrican 1047297sheries to employment and food security Ocean Coast Manage 11172ndash81
Berkes F Folke C 1998 Linking social and ecological systems for resilience andsustainability In Berkes F Folke C (Eds) Linking Social and EcologicalSystems Management Practices and Social Mechanisms for Building ResilienceCambridge University Press Cambridge pp 1ndash25
Bernier Q Meinzen-Dick R 2014 Resilience and social capital Building Resiliencefor Food and Nutrition Security Conference Paper No 4 International FoodPolicy Research Institute Washington DC 26 p
Bhattamishra R Barrett C 2010 Community-Based risk managementarrangements a review World Dev 38 (7) 923ndash932
Boarini R Kolev A McGregor JA 2014 Measuring well-being and progress incountries at different stages of development towards a more universalconceptual framework OECD Working Paper No 235 Organisation forEconomic Co-operation and Development Development Center
ndash Better Life
Initiative Paris 59 p
Boyd E Osbahr H Ericksen P Tompkins E Carmen Lemos M Miller F 2008Resilience and
lsquoclimatizingrsquo development examples and policy implicationsDevelopment 51 390ndash396
Cam1047297eld
L
McGregor
JA
2005
Resilience
and
wellbeing
in
developing
countriesIn Ungar M (Ed) Handbook for Working with Children and Youth Pathwaysto Resilience Across Cultures and Contexts Sage Publications Thousand OaksCA
Cam1047297eld
L
Ruta
D
2007
Translation
is
not
enough
using
the
Global
PersonGenerated Index (GPGI) to assess individual quality of life in BangladeshThailand and Ethiopia Qual Life 16 (6) 1039ndash1051
Carter M Little P Mogues T Negatu W 2007 Poverty traps and natural disastersin Ethiopia and Honduras World Dev 35 (5) 835ndash856
Cleaver
F
2005
The
inequality
of
social
capital
and
the
reproduction
of
chronicpoverty World Dev 33 (6) 893ndash906
Constas M Frankenberger T Hoddinott J 2014a Resilience measurementprinciples toward an agenda for measurement design Resilience MeasurementTechnical Working Group Technical Series No 1 Food Security informationNetwork Rome
Constas MT Frankenberger J Hoddinott N Mock D Romano C Beacuteneacute DMaxwell 2014b A common analytical model for resilience measurementcausal framework and methodological options Food Security InformationNetwork (FSIN) Technical Series No 2 World Food Programme Rome
Coulthard S 2011 More than just access to 1047297sh the pros and cons of 1047297sherparticipation
in
a
customary
marine
tenure
(Padu)
system
under
pressure
MarPolicy 35 405ndash412
DFID 2011 De1047297ning Disaster Resilience A DFID Approach Paper Department forInternational Development London pp 20
Dercon S Hoddinott J Woldehanna T 2005 Shocks and consumption in 15ethiopian
villages
1999ndash2004
J
Afr
Econ
14
(4)
559ndash585Dercon S 1996 Risk crop choice and savings evidence from Tanzania Econ Dev
Cult Change 44 (3) 485ndash513Duit A Galaz V Eckerberg K 2010 Governance complexity and resilience Glob
Environ Change 20 (3) 363ndash368Eriksen
SEH
Silva
JA
2009
The
vulnerability
context
of
a
savannah
area
inMozambique household drought coping strategies and responses to economicchange Environ Sci Policy 12 (1) 33ndash52
Fafchamps M Lund S 2003 Risk-Sharing networks in rural Philippines J DevEcon 71 (2) 261ndash287
Frankenberger T Nelson S 2013 Background Paper for the Expert Consultation onResilience
Measurement
for
Food
Security
TANGO
International
Rome
Foodand Agricultural Organization and World Food Program
Heltberg R Siegel PS Jorgensen SL 2009 Addressing human vulnerability toclimate change towards a
lsquono-regretsrsquo approach Glob Environ Change 19 89ndash99
Hoddinott
J
Dercon
S
Krishnan
P
2009
Networks
and
informal
mutual
supportin 15 ethiopian villages a description In Kirsten JF Dorward AR Poulton CVink N (Eds) Institutional Economics Perspectives on African AgriculturalDevelopment International Food Policy Research Institute Washington DC pp273ndash286
Hoddinott
J
2006
Shocks
and
their
consequences
across
and
within
households
inRural Zimbabwe J Dev Stud 42 (2) 301ndash321
Intergovernmental Panel on Climate Change (IPCC) 2012 In Field CB Barros VStocker TF Qin D Dokken DJ Ebi KL Mastrandrea MD Mach KJPlattner G-K Allen SK Tignor MMidgley PM (Eds) Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation A SpecialReport of Working Groups I and II of the Intergovernmental Panel on ClimateChange Cambridge University Press Cambridge UK
Jackson T 2005 Motivating sustainable consumptionmdasha review of evidence onconsumer behaviour and behavioural change A Report to the Sustainable
Event type (Vietnam) Reduce
expenditures
Borrow
money
Reduce
Food
Change
1047297shing
strategy
Get
support
Increase
1047297shing
effort
Diversi1047297cation Seek new
collaboration
Migration Exit the
1047297shery
Sell
assets
Total
Others (aggregated) 4 7 4 6 3 0 1 3 0 0 2 30
Erosion 2 4 2 1 6 2 2 2 3 1 25
Catch reduced
suddenly
8 4 6 7 1 2 4 2 34
Gears lost 10 18 6 5 1 2 1 43
Cold wind prolongs 15 7 11 3 1 7 2 46
Typhoon
12
11
10
2
4
2
3
5
4
1
1
55
Illness
11 14
6
2
11
2
2
4
1
1
2
56Food price increase 20 17 19 2 8 5 1 72
Input price increase
continuously
47 39 33 21 40 5 6 16 1 208
Big boats compete
ground and catch
54 39 32 40 9 19 11 15 8 3 2 232
Catch
reduced
continuously
102
70
80
63
22
51
51
25
23
17
6
510
Total 285 230 209 152 105 91 87 75 39 23 15 1311
C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170 169
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
Development Research Network Centre for Environmental StrategiesUniversity of Surrey
Jones L Boyd E 2011 Exploring social barriers to adaptation insights fromWestern Nepal Glob Environ Change 21 (4) 1262ndash1274
Kallstrom HN Ljung M 2005 Social sustainability and collaborative learningAmbio 34 376ndash382
Kelty R Kelty R 2011 Human dimensions of a 1047297shery at a crossroads resourcevaluation identity and way of life in a seasonal 1047297shing community Soc NatResour
24
(4)
334ndash348Klein RJT Nicholls RJ Thomalla F 2003 Resilience to natural hazards how
useful is this concept Environ Hazards 5 35ndash45
Krosnick
JA
Fabrigar
LR
1997
Designing
rating
scales
for
effective
measurementin surveys In Lyberg L Biemer P Collins M de Leeuw E Dippo C SchwarzN
Trewin
D
(Eds)
Survey
Measurement
and
Process
Quality
John
Wiley
andSons Inc New York NY pp 141ndash164
Leichenko R OrsquoBrien K 2008 Environmental Change and Globalization DoubleExposures Oxford University Press New York
Marschke M Berkes F 2006 Exploring Strategies that build livelihood resiliencea case from Cambodia Ecol Soc 11 (1) httpwwwecologyandsocietyorgvol11iss1art42
McGregor JA Cam1047297eld L Woodcock A 2009 Needs wants and goals wellbeingquality
of
life
and
public
policy
Appl
Res
Qual
Life
4
135ndash154McGregor JA 1994 Village credit and the reproduction of poverty in rural
Bangladesh In Acheson J (Ed) Economic Anthropology and the NewInstitutional Economics University Press of AmericaSociety for EconomicAnthropology Washington pp 261ndash281 (Chapter)
McGregor
JA
2011
Reimagining
development
through
the
crisis
watch
initiative
IDS Bull 42 (5) 17ndash23McLaughlin P Dietz T 2007 Structureagency and environment toward an
integrated perspective on vulnerability Glob Environ Change 39 (4) 99ndash111Meyer MA 2013 Social capital and resilience in the context of disaster social
capital
and
collective
ef 1047297cacy
for
disaster
resilience
connecting
individualswith communities and vulnerability with resilience in hurricane-pronecommunities in Florida PhD Dissertation Department of sociology Coloradostate University Fort Collins Colorado (311 p)
Mills DJ Adhuri D Phillips M Ravikumar B Padiyar AP 2011 Shocks recoverytrajectories and resilience among aquaculture-dependent households in post-tsunami
Aceh
Indonesia
Local
Environ
Int
J
Justice
Sustain
16
(5)
425ndash444Morduch J 1995 Income smoothing and consumption smoothing J Econ
Perspect 9 (3) 103ndash114Morris S Carletto C Hoddinott J Christiaensen L 2000 J Epidemiol Commun
Health 54 381ndash387Myers
RA
Worm
B
2003
Rapid
worldwide
depletion
of
predatory 1047297sh
communities Nature 423 280ndash283Nakagawa Y Shaw R 2004 Social capital a missing link to disaster recovery Int J
Mass
Emerg
Disasters
22
(1)
5ndash
34Nussbaum MC 2001 Adaptive preferences and womenrsquos options Econ Philos 1767ndash88
Oslashstergaard N Reenberg A 2010 Cultural barriers to climate change adaptation acase study from Northern Burkina Faso Glob Environ Change 20 (1) 142ndash152
OrsquoBrien K Leichenko R 2000 Double exposure assessing the impacts of climatechange within the context of economic globalization Glob Environ Change 10221ndash232
OrsquoBrien K Eriksen S Sygna L Naess LO 2006 Questioning complacencyclimate change impacts vulnerability and adaptation in Norway AMBIO JHum Environ 35 (2) 50ndash56
OrsquoBrien K Quilan T Ziervogel G 2009 Vulnerability interventions in the contextof multiple stressors lessons from the Southern Africa vulnerability initiative(SAVI) Environ Sci Policy 12 23ndash32
OrsquoRiordan T Jordan A 1999 Institutions climate change and cultural theorytowards a common analytical framework Glob Environ Change 9 (2) 81ndash93
Pain A Levine S 2012 A conceptual analysis of livelihoods and resilienceaddressing the
lsquoinsecurity of agency HPG Working Paper OverseasDevelopment Institute Humanitarian Policy Group London
Pauly D Christensen V Dalsgaard Froese JR Torres F 1998 Fishing downmarine food webs Science 279 (5352) 860ndash863
Pelling M Manuel-Navarrete D 2011 From resilience to transformation theadaptive cycle in two Mexican urban centersEcol Soc 16 (2)11 (online) httpwwwecologyandsocietyorgvol16iss2art11
Prowse
M
Scott
L
2008
Assets
and
adaptation
an
emerging
debate
IDS
Bull
39(4) 42ndash52
Putzel J 1997 Accounting for the lsquodark sidersquo of social capital reading Robert
Putnam
on
democracy
J
Int
Dev
9
(7)
939ndash949
Quinn CH Ziervogel G Taylor A Takama T Thomalla F 2011 Coping withmultiple
stresses
in
rural
South
Africa
Ecol
Soc
16
(3)
doihttpdxdoiorg105751ES-04216-160302
Reid P Vogel C 2006 Living and responding to multiple stressors in South Africamdashglimpses from KwaZulu-Natal Glob Environ Change 16 (2) 195ndash206
Roncoli C Ingram K Kirshen P 2001 The costs and risks of coping with droughtlivelihood
impacts
and
farmersrsquo
responses
in
Burkina
Faso
Clim
Res
19
119ndash132
Schwarz AM Beacuteneacute C Bennett G Boso D Hilly Z Paul C Posala R Sibiti SAndrew N 2011 Vulnerability and resilience of rural remote communities toshocks and global changes empirical analysis from the Solomon Islands GlobEnviron Change 21 1128ndash1140
Sinha
S
Lipton
M
Yaqub
S
2002
Poverty
and
damaging 1047298uctuations
how
dothey relate J Asian Afr Stud 37 (2) 186ndash243
Tansey J OrsquoRiordan T 1999 Cultural theory and risk a review Health Risk Soc 171ndash90
Teschl M Comim F 2005 Adaptive preferences and capabilities somepreliminary
conceptual
explorations
Rev
Soc
Econ
63
(2)
229ndash247
Trimble M Johnson D 2013 Artisanal 1047297shing as an undesirable way of life Theimplications for governance of 1047297shersrsquo wellbeing aspirations in coastal Uruguayand southeastern Brazil Mar Policy 37 37ndash44
Turner BL Kasperson RE Matson P McCarthy JJ Corell RW Christensen LEckley
N
Kasperson
JX
Luers
A
Martello
ML
Polsky
C
Pulsipher
ASchiller A 2003 A framework for vulnerability analysis in sustainabilityscience Proc Natl Acad Sci 100 (14) 8074ndash8079
Vigderhous G 1977 The level of measurement and
lsquoPermissiblersquo statistical analysisin social research Pac Sociol Rev 20 (1) 61ndash72
WFP 2013 Building Resilience Through Asset Creation Resilience and PreventionUnit
Policy
Programme
and
Innovation
Division
World
Food
Program
Rome(23 p)
Walker B Carpenter S Anderies J Abel N Cumming GS Janssen M Lebel LN J Peterson GD Pritchard R 2002 Resilience management in social-ecological systems a working hypothesis for a participatory approach ConservEcol
6
(1)
14Weber EU 2010 What shapes perceptions of climate change Clim Change 1 (3)
332ndash342
Wolf
J
Adger
WN
Lorenzoni
I
Abrahamson
V
Raine
R
2010
Social
capitalindividual responses to heat waves and climate change adaptation an empiricalstudy
of
two
UK
cities
Glob
Environ
Change
20
44ndash52Wood G 2003 Staying secure staying poor the Faustian bargain World Dev 31
(3) 455ndash471World Bank 2011 Building Resilience and Opportunities World Bankrsquos Social
Protection and Labour Strategy 2012ndash2022 World Bank Washington DCYamano T Alderman H Christiaensen L 2003 Child Growth Shocks and Food
Aid in Rural Ethiopia World Bank Washington DCZimmerman F Carter M 2003 Asset smoothing consumption smoothing and the
reproduction of inequality under risk and subsistence constraints J Dev Econ71 233ndash260
von Grebmer K Headey D Beacuteneacute C Haddad L et al 2013 Global Hunger IndexThe Challenge of Hunger Building Resilience to Achieve Food and NutritionSecurity Welthungerhilfe International Food Policy Research Institute andConcern Worldwide Bonn Washington DC and Dublin
170 C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
when all events are aggregated households are hit by a new event
of some kind every 485 days that is every 16 months
42 Household response analysis
The next step was to document and analyse the various types of
strategies that households employed in the face of shocks and
stressors In the resilience analysis framework (Fig 1) this
corresponds to the
lsquoresponse analysisrsquo component
Fig 4 presents the event-response matrices for the four country
case studies (computed for the ten most cited events per country)
The colour codes correspond to the four categories described in
Table 1 coping strategies social-relation based strategies 1047297shery-
related strategies and non-1047297shery-related strategies
The matrices show that coping strategies are the most frequent
responses put in place by households Amongst coping strategies
reduction of food consumption and reduction of general expenses
were commonly adopted while asset selling was notable for being
seldom adopted except in Ghana Beyond the generic pattern of
0 005 01 015 02 025 03 035
Others
High de
Destruconlossthe of fishing gear
Sudden change in sea condion
Slow increase in input prices
Major health problem
Death
Flood
Rapid (peak) increase in input prices
Decline in fish price
Sudden decli ne in catch
Slow decline in catch
Slow increase in food prices
Important change in fishing techniques
Any other fishery rela ted issue
unpredictable c hanges in weather
Hurricane
Percentage (total = 100)
Fiji
ST
MT
LT
0 005 01 015 02 025 03
Others
Increase in Food Price
Storm and strong winds
Unpred weather change
Accident Disability
Change in sea condion
Loss of financial assets
Loss of other assetsLoss fishing ground
Flood
Fish price increase
Sick family member
Death of family member
Destrucon The Loss gear
Input prices increase
Change in fishing techniques
Fuel shortage
Slow decline in catch
Percentage (total = 100)
Ghana
ST
MT
LT
0 005 01 015 0
Others
Slow but constant increase in input prices
Death of a family m ember
Other major weather event
Sudden change in sea condion
Flood
Sudden decline in catch
Loss of other assets other than fishing gear
Major health problem (sickness)
Decline in fish price
More unpredictable changes in weather paern
Important change in fishing techniquesSlow decline in catch
Limitaons-Harbour
New constraining fishing regulaon
Destruconlossthe of fishing gear
Rapid (peak) increase in input prices
Hurricane tropical storm
Perccentage (total = 100)
Sri Lanka
ST
MT
LT
0
005
01
015
02
025
03
035
04
045
Others
Lost assets
Accident
Erosion
Catch r educed suddently
Gears lost
Cold wind prolongs
Typhoon
Illness
Food price increase
Input price increa se connuously
Big boats compete ground and catch
Catch reduced connuously
Percentage (total = 100)
Vietnam
ST
MT
LT
Fig 2 Adverse event inventory for the four countries Events have been grouped and colour-coded into three categories short and unpredictable shocks (ST) (ii) medium-
term stressors that last several months andor are recurrent (MT) and (iii) long-term trends (LT)
0 10 20 30
Annually
On a connuous (daily) basis
Every 5 years
Bi-annually
Quarterly basis
Weekly basis
Monthly basis
Every two-year
Every 10 years
Every 20 year or less oen
Percentage of responses (total = 100)
(c) Event frequency
0
10
20
30
40
50
60
70
1 2 3 4 5
P e r c e n t a g e o f r e s p o n s e s ( t o t a l = 1 0 0 )
5-point scale rang
(b) Event severity
very bad lt ---------------------------------- gt posive
0
10
20
30
40
1 2 3 4 5
P e r c e n t a g e o f r e s p o n s e s ( t o t a l = 1 0 0 )
Fig 4 Event-response matrices for the four country case studies The numbers in the column are percentage of total responses ranked from the most (left) to the least (right)
adopted
and
colour-coded
using
the
typology
presented
in
Table
1 Full
details
are
provided
in
Appendix
A
Table 4
Average number of responses per event at the community level
Country Community Mean Std Err [95 Conf Interval]
Fiji A 27 022 232 317
B 26 007 244 272
Ghana C 43 018 389 461
D 39 016 359 421
Sri
Lanka
E
55
020
514
594F 76 026 707 809
Vietnam G 34 012 319 367
H 35 019 308 383
Total
(N
=
1868)
46
005
451
474
C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170 159
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
Resilience outcomes were explored using psychometric tech-
niques where households were asked to self-assess the degree of
recovery they managed to achieve for each of the adverse events
they had experienced in the past (see details in Table 2) The
answers provided by the respondents to the 1047297rst two questions of
the resilience analysis (self-recovery from past event and self-
recovery compared to the rest of the community) were used to
create a resilience index (RI) computed as the product of the two
scores As a result of the calculation process RI is an integer varying
between 1 and 30 where low values indicate low level of resilienceto a speci1047297c event while higher values indicate higher levels of
resilience
We then used this resilience index to explore the last remaining
working hypothesis of this research that is that
lsquosocial capital is
importantrsquo- ie the (intuitive) idea that households or communi-
ties characterized by higher level of social capital are able to draw
on social capital to help themselves (and others) in the aftermath
of an adverse event To analyse the resilience outcomes and explore
in particular this last hypothesis a three-level mixed effect linear
model was run where the resilience index was tested against a
series of 1047297xed and random factors used as independent explana-
tory variables Because the communities are nested within the
countries a three-level (hierarchical) model was
1047297tted with
random intercepts at both country and community-within-
country levels Random coef 1047297cients were also accounted for at
the country level on the Quality of Life (QoL) factors to re1047298ect
country speci1047297c effects More speci1047297cally the model was of the
form
RI vc frac14 b0 thorn b1Shockvc thorn b2Respvc thorn b3QoLvc thorn b4HH vc thorn g 1W c thorn g 2 Z vc thorn
evc
where the subscripts v and c hold for village (community) and
country respectively Shockvc is the covariate matrix for the
1047297xed
effect
b1 of the impacts of event e on individual household Respvc
is the covariate matrix for the 1047297xed effect b2 of the responses put in
places by the household QoLe is the covariate matrix for the
1047297xed
effect b3 of the Quality of Life scores recorded for each household
HH e is the matrix of variables and dummies controlling for
household characteristics W c is the covariate matrix for the cluster
random effect at the country level and Z vc is the covariate matrix
for the cluster random effect at the community level The details of
the different categories of variables included in the model are
provided in Table 6
Results of the model estimations including details of both
1047297xed and random effect speci1047297cations and diagnostic checking-
are presented in Table 7 The model highlights a series of important
1047297ndings First the degree of severity of the shock and the
disruptive impact on income are the twoshock variables that have
0
10
20
30
40
50
60
70
80
90
F o o d
E x p e n s e s
M o n e y
A s s e s t
S u p p o r t
C o l l a b o r a o n
D i v e r s i fi c a o n
M i g r a o n
E x i t
C h a n g e
I n c r e a s e
P e r c e n t a g e o f h o u s e h o l d s ( )
Response typology (Vietnam)
Boom 40
Top 40
0
01
02
03
04
05
06
07
F o o d
E x p e n s e s
M o n e y
A s s e t s
S u p p o r t
C o l l a b o r a o n
D i v e r s i fi c a o n
M i g r a o n
E x i t
C h a n g e
I n c r e a s e
P e r c e n t a g e o f h o u s e h o l d s ( )
Response typology (Fiji)Boom 40
Top 40
Fig 5 Comparative analysis of the responses adopted by the bottom (poorest) and top (wealthiest) 40 of the households when affected by the same event illustration
from Vietnam and Fiji Code of the responses
ldquoFoodrdquo = Reduce food consumption
ldquoExpensesrdquo = Reduce family general expenses
ldquoMoneyrdquo = Borrow money
ldquoAssetsrdquo = Sell
family assets
ldquoSupportrdquo= Seek for support from friends and peers
ldquoCollaborationrdquo= Develop new collaboration within the community
ldquoDiversi1047297cationrdquo = Invest in non-
1047297shery activities ldquoMigrationrdquo = Temporary permanently migration one or several members of the family ldquoExitrdquo = Exit the 1047297shery start a new joblivelihoodldquoChangerdquo = Change 1047297shing strategies
ldquoIncreaserdquo = Increase 1047297shing effort
160 C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
The type of responses adopted by households was included in
the model to test whether the level of resilience of households is
effectively in1047298uenced by those responses Amongst the 11 types of
responses tested three have statistically signi1047297cant signs engag-
ing
in
new
collaboration
(negative
sign
P
=
0001)
increasing1047297shing effort (positive P lt 00001) and quitting the
1047297shery
(negative P = 0047) The negative correlation found between
household resilience and the strategy that consists of forming new
collaboration may be dif 1047297cult to interpret as it can re1047298ect many
highly contextual factors The two others responses and the signs
of their correlations (one negative sign for leaving the sector and
one positive sign for increasing 1047297shing effort) are initially
disturbing but eventually not too surprising Disturbing
1047297rst
because this
1047297nding does not lead to the type of long-term
behaviours that appeal to policy makers and 1047297shery managers On
the contrary they would rather see 1047297shing effort reductions and
exit strategies more often adopted by
1047297shers in particular in the
context of the current world
1047297shery crisis Not surprising however
because this result is in line with what one could expect from
1047297sherfolks after an adverse event in the face of a long-term stress
(such
as
the
drop
in
income
following
a
continuous
decline
in
1047297shcatch) or a sudden need for cashrevenues (as a consequence of
eg destruction of 1047297shing gear induced by bad weather or the
need to pay health bills)
1047297shers are often observed to alter their
1047297shing activities to make up for these events usually by changing
adjusting their 1047297shing strategy (eg switching between targeted
species andor
1047297shing gear) or increasing their
1047297shing effort (eg
investing in more ef 1047297cient
1047297shing gear increasing the quantity of
gear used or increasing the number of days at sea) in an attempt to
generate more cash In that context it is not surprising that the
majority of 1047297shing households interviewed in this research
consider that their ability to
lsquobounce back following an adverse
event was enhanced when they increase their 1047297shing effort
Additionally given what we know about their strong sense of
identity
(Kelty
and
Kelty
2011
Trimble
and
Johnson
2013) but
alsothe importance of peer-pressure and reputation (see eg Beacuteneacute and
Tew1047297k 2001) quitting the 1047297shery would certainly be perceived by
many 1047297shers as a failure thus the negative correlation between
(perceived) resilience and leaving the sector
The next category of variables which was investigated through
the model was the Quality of Life indicators (see Table 3 for a
recall) A reasonable hypothesis although not explicitly formu-
lated in the
lsquoworking hypotheses section above- is that some of
these QoL indices may have a positive effect on the ability of
households to handle and recover from adverse events One can
indeed assume that households satis1047297ed in many of the
dimensions of wellbeing which they considers important (such
as say access to health services or to public infrastructure) may
feel better equipped to reactrespond to any particular event than
Table 5
Top comparison of propensities to adopt particular types of responses for households characterized by high (N = 224) and low (N = 235) subjective resilience Bottom
comparison of the two same groups in terms of asset levels education and age of the household head
Responses subjective
resilience
level
Mean [95 Conf
Interval]
test resulta
Coping strategies High 198 1840 2136 t = 43037 Pr(|T| gt |
t|) = 0000
Low 245 2311 2596
Social-relation-based strategies High 083 0738 0927 t = 05187 Pr(|T| gt |
t|) = 0604
Low 086 0787 0943
Fishing-related strategies High 083 0732 0935 t = 03267 Pr(|T| gt |
t|)
=
0744
Low 081 0715 0906
Non-1047297shery
strategies
High
067
0559
0794
t
=
35599
Pr(|T|
gt
|
t|) = 0000
Low 042 0341 0502
Household characteristics
Asset High 768 7218 8157 t = 08882 Pr(|T| gt |
t|) = 0374
Low 739 6938 7848
Education High 796 7338 8599 t = 10186 Pr(|T| gt |
t|)
=
0308
Low 750 6857 8147
Age High 4688 45377 48391 t = 01332 Pr(|T| gt |
t|) = 0894
Low 4702 45570 48482
p
lt 5
p
lt 1
p
lt 1
a mean difference unpaired t -test Ho Diff = 0 Ha diff 6frac14 0
C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170 161
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
diversif non 1047297sher diversi1047297cation dummy 1 = yes
exit_1047297sh exit the 1047297shery sector dummy 1 = yes
migrat migrate dummy 1 = yes
quality of life indices
index_incom
income
index
ordinal
variable
coded
[-6
+6]
ndash6
=
very
poor
+6
=
very
strong
index_livelih livelihood index ordinal variable coded [-6 +6] ndash6 = very poor +6 = very strongindex_housing housing and infrastructure index ordinal variable coded [-6 +6] ndash6 = very poor +6 = very strong
index_educ education index ordinal variable coded [-6 +6]
ndash6 = very poor +6 = very strong
index_soc social capital index ordinal variable coded [-6 +6]
ndash6 = very poor +6 = very strong
index_health health index ordinal variable coded [-6 +6] ndash6 = very poor +6 = very strong
ind_emp empowerment index ordinal variable coded [-6 +6]
ndash6 = very poor +6 = very strong
index_soc_cris social capital index in time of crisis
ndash6 = very poor +6 = very strong
index_emp_cris empowerment index in time of crisis
ndash6 = very poor +6 = very strong
index_spirit index of spirituality
ordinal variable coded [-6 +6]
ndash6 = very poor +6 = very strong
household characteristics
HH head sex sex of household head dummy 1 = female
HH
head
age
age
of
household
head
age
in
years
HH head educ level of education of the household head 0 = no education 20 = post-graduate level
HH size size of household number of members (not adjusted for age)
log_asset household assets (log-transformed) value of household assets (proxy for wealth level)
community
resiliencecomm_recov level of recovery of the community
a Fitting a three level model requires two random-effect equations one for level three (country) and one for level two (community) with i = 1 nvc 1047297rst level of
observation (households) nested within k = 1 8 s level cluster (community) nested within j = 1 4 third level cluster (country)
162 C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
community level in the same way than the QoL indices that is by
averaging the scores obtained at the individual household level)
The best correlation was obtained with the QoL index of social
capital in time of crisis (R 2= 077 F = 0004) see Fig 6- suggesting
that communities with higher social capital in time of crisis are
also characterized by higher level of resilience
5 Discussion
Resilience has been increasingly recognized as a potentially
useful concept to help practitioners academics and policy-makers
better understand the links between shocks response and longer-
term development outcomes (Constas et al 2014a Beacuteneacute et al
2014) Incorporating resilience alongside vulnerability analysis can
contribute an essential element to societal ability to better prepare
for future shocks and stressors This paper argues that improving
our understanding of what contributes to or constitutes peoplersquos
resilience requires not only the development and
1047297eld-testing of
robust and measurable indices (Beacuteneacute 2013 Constas et al 2014b)
but also a better insight into the social factors including
knowledge perceptions and motivations- that in1047298uence and affect
individual and collective capacity to respond to shocks and
stressors
Our analysis conducted in eight 1047297shery-dependent communi-
ties from Fiji Ghana Sri Lanka and Vietnam reveals a series of
notable results in relation to these questions In considering these
outcomes it is important to 1047297rst take stock of potential limitations
pitfalls or biases in the study methodology Given the nature of the
1047297ndings two potential issues require further consideration First is
the question of how representative our sampling methodology
was It could be argued for instance that the observed low adoption
rates of non-1047297shery strategiesndash and in particular the low score of
the
lsquoexiting the
1047297sheryrsquo was driven by our sampling method
underrepresenting these groups as those who had effectively left
the 1047297shery were not included in the sample
The FGDs that preceded the household survey speci1047297cally
addressed this issue In Sri Lanka for instance the opening question
prompted participants (both men and women) to discuss whether
ldquo1047297shers in their community had ever left 1047297sheries due to their
inability to cope with adverse eventsrdquo The answer was that it
generally does not happen with the notable exception of someyoung
1047297shers who attempted to migrate to Australia through
illegal means If it occurred exiting the 1047297shery was said to be
temporary ldquothey may leave the village or 1047297shing but will come
back when the situation is favourablerdquo In Vietnam the sampling
was speci1047297cally designed to cover both
1047297shers and ex-1047297shers in
proportions represented in the community As a result 9 ex-1047297shers
were included in the sample Overall therefore although we were
unable to conceive of a completely representative sampling design
(in the statistical sense) the parallel information that was collected
in the FGDs and the individual households converge to suggest that
exiting the
1047297shery was not an option envisaged by the members of
these different communities and consequently that our sampling
was not too severely biased
0
2
4
6
8
10
12
14
16
-05 05 15 25
C o m m u n i t y l e v e l r e s i l i
e n c e i n d e x
Community level social capital in me of crisis
Fiji
Ghana
Sri Lanka
Vietnam
Fig 6 Correlation between social capital in time of crisis and resilience index
across the eight communities The straight line represents the linear relation
(R 2 = 077 F = 0004) and the bars are 95 con1047297dence intervals for each community
Random-effects parameters St Dev Std Err [95 Conf Interval]
country level
index_incom 043 024 0146 1266
index_livelih 051 027 0175 1464
index_housing 013 013 0018 0962
index_soc 039 024 0119 1303
index_soc_cris
078
038
0300
2009index_educ 015 013 0028 0834
const 090 067 0209 3861
community level
const 032 026 0066 1534
residuals 277 008 2617 2923
LR test vs linear regression chi2(7) = 3916 Prob gt chi2= 0000
p
lt 5
p
lt
1 p lt 1ma Fitting a three level model requires two random-effect equations one for level three (country) and one for level two (community) with i = 1 nvc 1047297rst level of
observation
(households)
nested
within
k
=
1
8
second
level
cluster
(community)
nested
within
j
=
1
4
third
level
cluster
(country)b The likelihood-ratio (LR) test comparing the nested mixed-effects model with the corresponding 1047297xed effect model con1047297rms the appropriate use of the mixed effect
model (chi2(7) = 3916 Prob gt chi2= 0000) and the Wald test con1047297rms that the independent variables are valid predictors (Wald chi2(45) = 59414 Prob gt chi2= 0000) A
speci1047297cation test performed on the 1047297xed effect model using a Pregibonrsquos goodness-of-link test shows good results (t = 077 P gt |t| = 0439)
c The dummy variables sev_event3 cat_event2 predict2 and comm_recov3 were omitted from the 1047297xed effect component for estimation purpose
Table 7 (Continued)
164 C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
The second potential limitation in our methodology relates to
the way the level of resilience of the households was assessed
While psychometric measurements are reliable and their results
replicable and testable when correctly implemented (Vigderhous
1977) one could fear that their use in the speci1047297c case of resilience
measurement could be subject to the effect of adaptive preference
that is the deliberate or re1047298exive process by which people adjust
their expectations and aspirations when trying to cope with
deterioration in living conditions (see eg Nussbaum 2001 Teschl
and Comim 2005) In our case this means that households
undergoing a degree of adaptive preference could have over-
estimated their ability to recover Although this risk is present we
tried to mitigate (or to reduce) it by introducing a qualifying
element in each of the coded answers of the resilience question-
naire so that respondents would have to associate the
1047297rst part of
their answer ldquoI have fully recoveredrdquo with a particular lsquoframe of
reference or quali1047297er (eg ldquoand it was not too dif 1047297cultrdquo) This frame
determined how they comprehend the questions being asked and
reduced the risk of the respondent simply relying on emotional
elements to answer these questions
Keeping in mind these potential limitations we now turn to
what we consider the most notable results of this research First is
the
lsquocumulative and continuous effect of shocks and stressors
whereby the impacts and disturbance of sequential shocksstressors and trends during the last 1047297ve years combine and
coalesce to create a constant non-stop stress We saw that the
nature and the source of events that were identi1047297ed by the
respondents in the four countries are all highly varied and
composite and reveal no speci1047297c clear pattern The events are a
combination of idiosyncratic and covariant sudden shocks and
long-term continuous trends Some are predictable while others
are totally unexpected All affect households simultaneously and
on an almost continuous basis The data suggests in particular that
on average households are hit by a new event every 16 months
This result calls into questions the framework generally used to
conduct shock or vulnerability assessment Often the approach has
been to disaggregate the problems people face and focus on single
threats such as eg 1047298ood or increase in food prices in order todevelop a clearer understanding of the impact of these particular
shocks and the ways people respond to them This approach has
been challenged however by a growing number of scholars who
argue that the reality households face on a daily basis is not linear
and mono-dimensional (OrsquoBrien and Leichenko 2000 Eriksen and
Silva 2009 Quinn et al 2011 McGregor 2011) Instead they argue
risks and vulnerability are often the product of multiple stressors
(Turner et al 2003 OrsquoBrien et al 2009) where social economic
political and biophysical factors interact combine and reinforce
each other to create a complex and dynamic multi-stressor multi-
shock environment (Reid and Vogel 2006 Adger 2006) Our
results corroborate this new interpretation
In line with this our analysis also shows that most households
engage in a suite of responses to a given shock On average
households adopted more than 4 types of responses to a particular
event This last result does not simply imply a rethinking of the way
shock or vulnerability assessments are conceptualized and
conducted see eg Turner et al (2003) or Leichenko and OrsquoBrien
(2008) It also demonstrates that the mental model (shock
gt response gt recovery) which is widely accepted in the
resilience literature is too simplistic and possibly misleading in
the sense that a state of (full) recovery may not exist This is at least
what was observed for the households included in our research
these households did not seem to have the chance or the time to
fully recover from one particular event before being affected by the
next Instead they were caught in what we could characterize as ldquoaconstant state of incomplete recoveringrdquo from new shocks and
stressors as illustrated in Fig 7
The next entry point in this discussion is wealth Our mixed
effect model (Table 7) shows that wealth was positively correlated
with household resilience Wealth has been identi1047297ed in the
literature as a key factor in strengthening the resilience of
households (Prowse and Scott 2008 WFP 2013) Analysis of
rural Ethiopian households hit by drought for instance showed that
while better-off households could sell livestock to smooth
consumption the poorer often tried to hold on to their livestock
at the expense of food consumption to preserve their options for
rebuilding herds The same study also shows that in the aftermath
of the hurricane Mitch in Honduras the relatively wealthy
households were able to rebuild their lost assets faster than thepoorest households for whom the effects of the hurricane were of
longer duration and felt much more acutely (Carter et al 2007) In
Fig 7 Left Current conceptualisation of resilience shock gt response gt recovery as presented in the literature [here redrawn from Carter et al 2007] Right actual
situation where the multi-stressor multi-shock environment induces that households are in a trajectory of continual and incomplete recovery Not represented here are the
multi-response
strategies
put
in
place
by
households
to
respond
to
these
adverse
events
C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170 165
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
disaster resilience National Disaster Resilience Roundtable Report 20September 2012 Melbourne Australia 36 p
Adger NW Dessai S Goulden M Hulme M Lorenzoni I Nelson DR Naess LO Wolf J Wreford A 2009 Are there social limits to adaptation to climatechange
Clim
Change
93
335ndash354Adger WN 2003 Social capital collective action and adaptation to climate
change Econ Geogr 79 (4) 387ndash404Adger WN 2006 Vulnerability Glob Environ Change 16 268ndash281Aldrich D 2010 Fixing recovery social capital in post-Crisis resilience J Homeland
Secur 6 1ndash10Ayers
J
Forsyth
T
2009
Community-based
adaptation
to
climate
changestrengthening resilience through development Environment 51 23ndash31
Beacuteneacute C Tew1047297k A 2001 Fishing effort allocation and 1047297shermenrsquos decision-makingprocess in a multi-species small-scale 1047297shery analysis of the conch and lobster1047297shery in Turks and Caicos Islands Hum Ecol 29 (2) 157ndash186
Beacuteneacute
C
Evans
L
Mills
D
Ovie
S
Raji
A
Ta1047297da
A
Kodio
A
Sinaba
F
Morand
PLemoalle J Andrew N 2011 Testing resilience thinking in a poverty contextexperience from the Niger river basin Glob Environ Change 21 (4) 1173ndash1184
Beacuteneacute C Godfrey-Wood R Newsham A Davies M2012 Resilience new utopia ornew tyranny
ndash Re1047298ection about the potentials and limits of the concept of
resilience
in
relation
to
vulnerability
reduction
programmes
IDS
Working
Paperno 405 Institute of Development Studies Brighton 61 p
Beacuteneacute C Newsham A Davies M Ulrichs M Godfrey-Wood R 2014 Resiliencepoverty and development J Int Dev 26 598ndash623
Beacuteneacute C Waid J Jackson-deGraffenried M Begum A Chowdhury M Skarin VRahman A Islam N Mamnun N Mainuddin K Shah MA 2015a Impact of climate-related
shocks
and
stresses
on
nutrition
and
food
security
in
ruralBangladesh Dhaka World Food Programme 119 p
Beacuteneacute C Frankenberger T Nelson S 2015b Design monitoring and evaluation of resilience interventions conceptual and empirical considerations IDS WorkingPaper no459 Institute of Development Studies 23 p
Beacuteneacute
C
2013
Towards
a
quanti1047297able
measure
of
resilience
IDS
Working
Paper
434Institute of Development Studies Brighton 27 p
Bandura A 1977 Self-ef 1047297cacy toward a unifying theory of behavioral changePsychol Rev 84 191ndash215
Baulch R Hoddinott J 2000 Economic mobility and poverty dynamics indeveloping countries J Dev Stud 36 (6) 1ndash23
Belhabib
D
Sumaila
UR
Pauly
D
2015
Feeding
the
poor
contribution
of
WestAfrican 1047297sheries to employment and food security Ocean Coast Manage 11172ndash81
Berkes F Folke C 1998 Linking social and ecological systems for resilience andsustainability In Berkes F Folke C (Eds) Linking Social and EcologicalSystems Management Practices and Social Mechanisms for Building ResilienceCambridge University Press Cambridge pp 1ndash25
Bernier Q Meinzen-Dick R 2014 Resilience and social capital Building Resiliencefor Food and Nutrition Security Conference Paper No 4 International FoodPolicy Research Institute Washington DC 26 p
Bhattamishra R Barrett C 2010 Community-Based risk managementarrangements a review World Dev 38 (7) 923ndash932
Boarini R Kolev A McGregor JA 2014 Measuring well-being and progress incountries at different stages of development towards a more universalconceptual framework OECD Working Paper No 235 Organisation forEconomic Co-operation and Development Development Center
ndash Better Life
Initiative Paris 59 p
Boyd E Osbahr H Ericksen P Tompkins E Carmen Lemos M Miller F 2008Resilience and
lsquoclimatizingrsquo development examples and policy implicationsDevelopment 51 390ndash396
Cam1047297eld
L
McGregor
JA
2005
Resilience
and
wellbeing
in
developing
countriesIn Ungar M (Ed) Handbook for Working with Children and Youth Pathwaysto Resilience Across Cultures and Contexts Sage Publications Thousand OaksCA
Cam1047297eld
L
Ruta
D
2007
Translation
is
not
enough
using
the
Global
PersonGenerated Index (GPGI) to assess individual quality of life in BangladeshThailand and Ethiopia Qual Life 16 (6) 1039ndash1051
Carter M Little P Mogues T Negatu W 2007 Poverty traps and natural disastersin Ethiopia and Honduras World Dev 35 (5) 835ndash856
Cleaver
F
2005
The
inequality
of
social
capital
and
the
reproduction
of
chronicpoverty World Dev 33 (6) 893ndash906
Constas M Frankenberger T Hoddinott J 2014a Resilience measurementprinciples toward an agenda for measurement design Resilience MeasurementTechnical Working Group Technical Series No 1 Food Security informationNetwork Rome
Constas MT Frankenberger J Hoddinott N Mock D Romano C Beacuteneacute DMaxwell 2014b A common analytical model for resilience measurementcausal framework and methodological options Food Security InformationNetwork (FSIN) Technical Series No 2 World Food Programme Rome
Coulthard S 2011 More than just access to 1047297sh the pros and cons of 1047297sherparticipation
in
a
customary
marine
tenure
(Padu)
system
under
pressure
MarPolicy 35 405ndash412
DFID 2011 De1047297ning Disaster Resilience A DFID Approach Paper Department forInternational Development London pp 20
Dercon S Hoddinott J Woldehanna T 2005 Shocks and consumption in 15ethiopian
villages
1999ndash2004
J
Afr
Econ
14
(4)
559ndash585Dercon S 1996 Risk crop choice and savings evidence from Tanzania Econ Dev
Cult Change 44 (3) 485ndash513Duit A Galaz V Eckerberg K 2010 Governance complexity and resilience Glob
Environ Change 20 (3) 363ndash368Eriksen
SEH
Silva
JA
2009
The
vulnerability
context
of
a
savannah
area
inMozambique household drought coping strategies and responses to economicchange Environ Sci Policy 12 (1) 33ndash52
Fafchamps M Lund S 2003 Risk-Sharing networks in rural Philippines J DevEcon 71 (2) 261ndash287
Frankenberger T Nelson S 2013 Background Paper for the Expert Consultation onResilience
Measurement
for
Food
Security
TANGO
International
Rome
Foodand Agricultural Organization and World Food Program
Heltberg R Siegel PS Jorgensen SL 2009 Addressing human vulnerability toclimate change towards a
lsquono-regretsrsquo approach Glob Environ Change 19 89ndash99
Hoddinott
J
Dercon
S
Krishnan
P
2009
Networks
and
informal
mutual
supportin 15 ethiopian villages a description In Kirsten JF Dorward AR Poulton CVink N (Eds) Institutional Economics Perspectives on African AgriculturalDevelopment International Food Policy Research Institute Washington DC pp273ndash286
Hoddinott
J
2006
Shocks
and
their
consequences
across
and
within
households
inRural Zimbabwe J Dev Stud 42 (2) 301ndash321
Intergovernmental Panel on Climate Change (IPCC) 2012 In Field CB Barros VStocker TF Qin D Dokken DJ Ebi KL Mastrandrea MD Mach KJPlattner G-K Allen SK Tignor MMidgley PM (Eds) Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation A SpecialReport of Working Groups I and II of the Intergovernmental Panel on ClimateChange Cambridge University Press Cambridge UK
Jackson T 2005 Motivating sustainable consumptionmdasha review of evidence onconsumer behaviour and behavioural change A Report to the Sustainable
Event type (Vietnam) Reduce
expenditures
Borrow
money
Reduce
Food
Change
1047297shing
strategy
Get
support
Increase
1047297shing
effort
Diversi1047297cation Seek new
collaboration
Migration Exit the
1047297shery
Sell
assets
Total
Others (aggregated) 4 7 4 6 3 0 1 3 0 0 2 30
Erosion 2 4 2 1 6 2 2 2 3 1 25
Catch reduced
suddenly
8 4 6 7 1 2 4 2 34
Gears lost 10 18 6 5 1 2 1 43
Cold wind prolongs 15 7 11 3 1 7 2 46
Typhoon
12
11
10
2
4
2
3
5
4
1
1
55
Illness
11 14
6
2
11
2
2
4
1
1
2
56Food price increase 20 17 19 2 8 5 1 72
Input price increase
continuously
47 39 33 21 40 5 6 16 1 208
Big boats compete
ground and catch
54 39 32 40 9 19 11 15 8 3 2 232
Catch
reduced
continuously
102
70
80
63
22
51
51
25
23
17
6
510
Total 285 230 209 152 105 91 87 75 39 23 15 1311
C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170 169
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
Development Research Network Centre for Environmental StrategiesUniversity of Surrey
Jones L Boyd E 2011 Exploring social barriers to adaptation insights fromWestern Nepal Glob Environ Change 21 (4) 1262ndash1274
Kallstrom HN Ljung M 2005 Social sustainability and collaborative learningAmbio 34 376ndash382
Kelty R Kelty R 2011 Human dimensions of a 1047297shery at a crossroads resourcevaluation identity and way of life in a seasonal 1047297shing community Soc NatResour
24
(4)
334ndash348Klein RJT Nicholls RJ Thomalla F 2003 Resilience to natural hazards how
useful is this concept Environ Hazards 5 35ndash45
Krosnick
JA
Fabrigar
LR
1997
Designing
rating
scales
for
effective
measurementin surveys In Lyberg L Biemer P Collins M de Leeuw E Dippo C SchwarzN
Trewin
D
(Eds)
Survey
Measurement
and
Process
Quality
John
Wiley
andSons Inc New York NY pp 141ndash164
Leichenko R OrsquoBrien K 2008 Environmental Change and Globalization DoubleExposures Oxford University Press New York
Marschke M Berkes F 2006 Exploring Strategies that build livelihood resiliencea case from Cambodia Ecol Soc 11 (1) httpwwwecologyandsocietyorgvol11iss1art42
McGregor JA Cam1047297eld L Woodcock A 2009 Needs wants and goals wellbeingquality
of
life
and
public
policy
Appl
Res
Qual
Life
4
135ndash154McGregor JA 1994 Village credit and the reproduction of poverty in rural
Bangladesh In Acheson J (Ed) Economic Anthropology and the NewInstitutional Economics University Press of AmericaSociety for EconomicAnthropology Washington pp 261ndash281 (Chapter)
McGregor
JA
2011
Reimagining
development
through
the
crisis
watch
initiative
IDS Bull 42 (5) 17ndash23McLaughlin P Dietz T 2007 Structureagency and environment toward an
integrated perspective on vulnerability Glob Environ Change 39 (4) 99ndash111Meyer MA 2013 Social capital and resilience in the context of disaster social
capital
and
collective
ef 1047297cacy
for
disaster
resilience
connecting
individualswith communities and vulnerability with resilience in hurricane-pronecommunities in Florida PhD Dissertation Department of sociology Coloradostate University Fort Collins Colorado (311 p)
Mills DJ Adhuri D Phillips M Ravikumar B Padiyar AP 2011 Shocks recoverytrajectories and resilience among aquaculture-dependent households in post-tsunami
Aceh
Indonesia
Local
Environ
Int
J
Justice
Sustain
16
(5)
425ndash444Morduch J 1995 Income smoothing and consumption smoothing J Econ
Perspect 9 (3) 103ndash114Morris S Carletto C Hoddinott J Christiaensen L 2000 J Epidemiol Commun
Health 54 381ndash387Myers
RA
Worm
B
2003
Rapid
worldwide
depletion
of
predatory 1047297sh
communities Nature 423 280ndash283Nakagawa Y Shaw R 2004 Social capital a missing link to disaster recovery Int J
Mass
Emerg
Disasters
22
(1)
5ndash
34Nussbaum MC 2001 Adaptive preferences and womenrsquos options Econ Philos 1767ndash88
Oslashstergaard N Reenberg A 2010 Cultural barriers to climate change adaptation acase study from Northern Burkina Faso Glob Environ Change 20 (1) 142ndash152
OrsquoBrien K Leichenko R 2000 Double exposure assessing the impacts of climatechange within the context of economic globalization Glob Environ Change 10221ndash232
OrsquoBrien K Eriksen S Sygna L Naess LO 2006 Questioning complacencyclimate change impacts vulnerability and adaptation in Norway AMBIO JHum Environ 35 (2) 50ndash56
OrsquoBrien K Quilan T Ziervogel G 2009 Vulnerability interventions in the contextof multiple stressors lessons from the Southern Africa vulnerability initiative(SAVI) Environ Sci Policy 12 23ndash32
OrsquoRiordan T Jordan A 1999 Institutions climate change and cultural theorytowards a common analytical framework Glob Environ Change 9 (2) 81ndash93
Pain A Levine S 2012 A conceptual analysis of livelihoods and resilienceaddressing the
lsquoinsecurity of agency HPG Working Paper OverseasDevelopment Institute Humanitarian Policy Group London
Pauly D Christensen V Dalsgaard Froese JR Torres F 1998 Fishing downmarine food webs Science 279 (5352) 860ndash863
Pelling M Manuel-Navarrete D 2011 From resilience to transformation theadaptive cycle in two Mexican urban centersEcol Soc 16 (2)11 (online) httpwwwecologyandsocietyorgvol16iss2art11
Prowse
M
Scott
L
2008
Assets
and
adaptation
an
emerging
debate
IDS
Bull
39(4) 42ndash52
Putzel J 1997 Accounting for the lsquodark sidersquo of social capital reading Robert
Putnam
on
democracy
J
Int
Dev
9
(7)
939ndash949
Quinn CH Ziervogel G Taylor A Takama T Thomalla F 2011 Coping withmultiple
stresses
in
rural
South
Africa
Ecol
Soc
16
(3)
doihttpdxdoiorg105751ES-04216-160302
Reid P Vogel C 2006 Living and responding to multiple stressors in South Africamdashglimpses from KwaZulu-Natal Glob Environ Change 16 (2) 195ndash206
Roncoli C Ingram K Kirshen P 2001 The costs and risks of coping with droughtlivelihood
impacts
and
farmersrsquo
responses
in
Burkina
Faso
Clim
Res
19
119ndash132
Schwarz AM Beacuteneacute C Bennett G Boso D Hilly Z Paul C Posala R Sibiti SAndrew N 2011 Vulnerability and resilience of rural remote communities toshocks and global changes empirical analysis from the Solomon Islands GlobEnviron Change 21 1128ndash1140
Sinha
S
Lipton
M
Yaqub
S
2002
Poverty
and
damaging 1047298uctuations
how
dothey relate J Asian Afr Stud 37 (2) 186ndash243
Tansey J OrsquoRiordan T 1999 Cultural theory and risk a review Health Risk Soc 171ndash90
Teschl M Comim F 2005 Adaptive preferences and capabilities somepreliminary
conceptual
explorations
Rev
Soc
Econ
63
(2)
229ndash247
Trimble M Johnson D 2013 Artisanal 1047297shing as an undesirable way of life Theimplications for governance of 1047297shersrsquo wellbeing aspirations in coastal Uruguayand southeastern Brazil Mar Policy 37 37ndash44
Turner BL Kasperson RE Matson P McCarthy JJ Corell RW Christensen LEckley
N
Kasperson
JX
Luers
A
Martello
ML
Polsky
C
Pulsipher
ASchiller A 2003 A framework for vulnerability analysis in sustainabilityscience Proc Natl Acad Sci 100 (14) 8074ndash8079
Vigderhous G 1977 The level of measurement and
lsquoPermissiblersquo statistical analysisin social research Pac Sociol Rev 20 (1) 61ndash72
WFP 2013 Building Resilience Through Asset Creation Resilience and PreventionUnit
Policy
Programme
and
Innovation
Division
World
Food
Program
Rome(23 p)
Walker B Carpenter S Anderies J Abel N Cumming GS Janssen M Lebel LN J Peterson GD Pritchard R 2002 Resilience management in social-ecological systems a working hypothesis for a participatory approach ConservEcol
6
(1)
14Weber EU 2010 What shapes perceptions of climate change Clim Change 1 (3)
332ndash342
Wolf
J
Adger
WN
Lorenzoni
I
Abrahamson
V
Raine
R
2010
Social
capitalindividual responses to heat waves and climate change adaptation an empiricalstudy
of
two
UK
cities
Glob
Environ
Change
20
44ndash52Wood G 2003 Staying secure staying poor the Faustian bargain World Dev 31
(3) 455ndash471World Bank 2011 Building Resilience and Opportunities World Bankrsquos Social
Protection and Labour Strategy 2012ndash2022 World Bank Washington DCYamano T Alderman H Christiaensen L 2003 Child Growth Shocks and Food
Aid in Rural Ethiopia World Bank Washington DCZimmerman F Carter M 2003 Asset smoothing consumption smoothing and the
reproduction of inequality under risk and subsistence constraints J Dev Econ71 233ndash260
von Grebmer K Headey D Beacuteneacute C Haddad L et al 2013 Global Hunger IndexThe Challenge of Hunger Building Resilience to Achieve Food and NutritionSecurity Welthungerhilfe International Food Policy Research Institute andConcern Worldwide Bonn Washington DC and Dublin
170 C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
Fig 4 Event-response matrices for the four country case studies The numbers in the column are percentage of total responses ranked from the most (left) to the least (right)
adopted
and
colour-coded
using
the
typology
presented
in
Table
1 Full
details
are
provided
in
Appendix
A
Table 4
Average number of responses per event at the community level
Country Community Mean Std Err [95 Conf Interval]
Fiji A 27 022 232 317
B 26 007 244 272
Ghana C 43 018 389 461
D 39 016 359 421
Sri
Lanka
E
55
020
514
594F 76 026 707 809
Vietnam G 34 012 319 367
H 35 019 308 383
Total
(N
=
1868)
46
005
451
474
C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170 159
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
Resilience outcomes were explored using psychometric tech-
niques where households were asked to self-assess the degree of
recovery they managed to achieve for each of the adverse events
they had experienced in the past (see details in Table 2) The
answers provided by the respondents to the 1047297rst two questions of
the resilience analysis (self-recovery from past event and self-
recovery compared to the rest of the community) were used to
create a resilience index (RI) computed as the product of the two
scores As a result of the calculation process RI is an integer varying
between 1 and 30 where low values indicate low level of resilienceto a speci1047297c event while higher values indicate higher levels of
resilience
We then used this resilience index to explore the last remaining
working hypothesis of this research that is that
lsquosocial capital is
importantrsquo- ie the (intuitive) idea that households or communi-
ties characterized by higher level of social capital are able to draw
on social capital to help themselves (and others) in the aftermath
of an adverse event To analyse the resilience outcomes and explore
in particular this last hypothesis a three-level mixed effect linear
model was run where the resilience index was tested against a
series of 1047297xed and random factors used as independent explana-
tory variables Because the communities are nested within the
countries a three-level (hierarchical) model was
1047297tted with
random intercepts at both country and community-within-
country levels Random coef 1047297cients were also accounted for at
the country level on the Quality of Life (QoL) factors to re1047298ect
country speci1047297c effects More speci1047297cally the model was of the
form
RI vc frac14 b0 thorn b1Shockvc thorn b2Respvc thorn b3QoLvc thorn b4HH vc thorn g 1W c thorn g 2 Z vc thorn
evc
where the subscripts v and c hold for village (community) and
country respectively Shockvc is the covariate matrix for the
1047297xed
effect
b1 of the impacts of event e on individual household Respvc
is the covariate matrix for the 1047297xed effect b2 of the responses put in
places by the household QoLe is the covariate matrix for the
1047297xed
effect b3 of the Quality of Life scores recorded for each household
HH e is the matrix of variables and dummies controlling for
household characteristics W c is the covariate matrix for the cluster
random effect at the country level and Z vc is the covariate matrix
for the cluster random effect at the community level The details of
the different categories of variables included in the model are
provided in Table 6
Results of the model estimations including details of both
1047297xed and random effect speci1047297cations and diagnostic checking-
are presented in Table 7 The model highlights a series of important
1047297ndings First the degree of severity of the shock and the
disruptive impact on income are the twoshock variables that have
0
10
20
30
40
50
60
70
80
90
F o o d
E x p e n s e s
M o n e y
A s s e s t
S u p p o r t
C o l l a b o r a o n
D i v e r s i fi c a o n
M i g r a o n
E x i t
C h a n g e
I n c r e a s e
P e r c e n t a g e o f h o u s e h o l d s ( )
Response typology (Vietnam)
Boom 40
Top 40
0
01
02
03
04
05
06
07
F o o d
E x p e n s e s
M o n e y
A s s e t s
S u p p o r t
C o l l a b o r a o n
D i v e r s i fi c a o n
M i g r a o n
E x i t
C h a n g e
I n c r e a s e
P e r c e n t a g e o f h o u s e h o l d s ( )
Response typology (Fiji)Boom 40
Top 40
Fig 5 Comparative analysis of the responses adopted by the bottom (poorest) and top (wealthiest) 40 of the households when affected by the same event illustration
from Vietnam and Fiji Code of the responses
ldquoFoodrdquo = Reduce food consumption
ldquoExpensesrdquo = Reduce family general expenses
ldquoMoneyrdquo = Borrow money
ldquoAssetsrdquo = Sell
family assets
ldquoSupportrdquo= Seek for support from friends and peers
ldquoCollaborationrdquo= Develop new collaboration within the community
ldquoDiversi1047297cationrdquo = Invest in non-
1047297shery activities ldquoMigrationrdquo = Temporary permanently migration one or several members of the family ldquoExitrdquo = Exit the 1047297shery start a new joblivelihoodldquoChangerdquo = Change 1047297shing strategies
ldquoIncreaserdquo = Increase 1047297shing effort
160 C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
The type of responses adopted by households was included in
the model to test whether the level of resilience of households is
effectively in1047298uenced by those responses Amongst the 11 types of
responses tested three have statistically signi1047297cant signs engag-
ing
in
new
collaboration
(negative
sign
P
=
0001)
increasing1047297shing effort (positive P lt 00001) and quitting the
1047297shery
(negative P = 0047) The negative correlation found between
household resilience and the strategy that consists of forming new
collaboration may be dif 1047297cult to interpret as it can re1047298ect many
highly contextual factors The two others responses and the signs
of their correlations (one negative sign for leaving the sector and
one positive sign for increasing 1047297shing effort) are initially
disturbing but eventually not too surprising Disturbing
1047297rst
because this
1047297nding does not lead to the type of long-term
behaviours that appeal to policy makers and 1047297shery managers On
the contrary they would rather see 1047297shing effort reductions and
exit strategies more often adopted by
1047297shers in particular in the
context of the current world
1047297shery crisis Not surprising however
because this result is in line with what one could expect from
1047297sherfolks after an adverse event in the face of a long-term stress
(such
as
the
drop
in
income
following
a
continuous
decline
in
1047297shcatch) or a sudden need for cashrevenues (as a consequence of
eg destruction of 1047297shing gear induced by bad weather or the
need to pay health bills)
1047297shers are often observed to alter their
1047297shing activities to make up for these events usually by changing
adjusting their 1047297shing strategy (eg switching between targeted
species andor
1047297shing gear) or increasing their
1047297shing effort (eg
investing in more ef 1047297cient
1047297shing gear increasing the quantity of
gear used or increasing the number of days at sea) in an attempt to
generate more cash In that context it is not surprising that the
majority of 1047297shing households interviewed in this research
consider that their ability to
lsquobounce back following an adverse
event was enhanced when they increase their 1047297shing effort
Additionally given what we know about their strong sense of
identity
(Kelty
and
Kelty
2011
Trimble
and
Johnson
2013) but
alsothe importance of peer-pressure and reputation (see eg Beacuteneacute and
Tew1047297k 2001) quitting the 1047297shery would certainly be perceived by
many 1047297shers as a failure thus the negative correlation between
(perceived) resilience and leaving the sector
The next category of variables which was investigated through
the model was the Quality of Life indicators (see Table 3 for a
recall) A reasonable hypothesis although not explicitly formu-
lated in the
lsquoworking hypotheses section above- is that some of
these QoL indices may have a positive effect on the ability of
households to handle and recover from adverse events One can
indeed assume that households satis1047297ed in many of the
dimensions of wellbeing which they considers important (such
as say access to health services or to public infrastructure) may
feel better equipped to reactrespond to any particular event than
Table 5
Top comparison of propensities to adopt particular types of responses for households characterized by high (N = 224) and low (N = 235) subjective resilience Bottom
comparison of the two same groups in terms of asset levels education and age of the household head
Responses subjective
resilience
level
Mean [95 Conf
Interval]
test resulta
Coping strategies High 198 1840 2136 t = 43037 Pr(|T| gt |
t|) = 0000
Low 245 2311 2596
Social-relation-based strategies High 083 0738 0927 t = 05187 Pr(|T| gt |
t|) = 0604
Low 086 0787 0943
Fishing-related strategies High 083 0732 0935 t = 03267 Pr(|T| gt |
t|)
=
0744
Low 081 0715 0906
Non-1047297shery
strategies
High
067
0559
0794
t
=
35599
Pr(|T|
gt
|
t|) = 0000
Low 042 0341 0502
Household characteristics
Asset High 768 7218 8157 t = 08882 Pr(|T| gt |
t|) = 0374
Low 739 6938 7848
Education High 796 7338 8599 t = 10186 Pr(|T| gt |
t|)
=
0308
Low 750 6857 8147
Age High 4688 45377 48391 t = 01332 Pr(|T| gt |
t|) = 0894
Low 4702 45570 48482
p
lt 5
p
lt 1
p
lt 1
a mean difference unpaired t -test Ho Diff = 0 Ha diff 6frac14 0
C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170 161
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
diversif non 1047297sher diversi1047297cation dummy 1 = yes
exit_1047297sh exit the 1047297shery sector dummy 1 = yes
migrat migrate dummy 1 = yes
quality of life indices
index_incom
income
index
ordinal
variable
coded
[-6
+6]
ndash6
=
very
poor
+6
=
very
strong
index_livelih livelihood index ordinal variable coded [-6 +6] ndash6 = very poor +6 = very strongindex_housing housing and infrastructure index ordinal variable coded [-6 +6] ndash6 = very poor +6 = very strong
index_educ education index ordinal variable coded [-6 +6]
ndash6 = very poor +6 = very strong
index_soc social capital index ordinal variable coded [-6 +6]
ndash6 = very poor +6 = very strong
index_health health index ordinal variable coded [-6 +6] ndash6 = very poor +6 = very strong
ind_emp empowerment index ordinal variable coded [-6 +6]
ndash6 = very poor +6 = very strong
index_soc_cris social capital index in time of crisis
ndash6 = very poor +6 = very strong
index_emp_cris empowerment index in time of crisis
ndash6 = very poor +6 = very strong
index_spirit index of spirituality
ordinal variable coded [-6 +6]
ndash6 = very poor +6 = very strong
household characteristics
HH head sex sex of household head dummy 1 = female
HH
head
age
age
of
household
head
age
in
years
HH head educ level of education of the household head 0 = no education 20 = post-graduate level
HH size size of household number of members (not adjusted for age)
log_asset household assets (log-transformed) value of household assets (proxy for wealth level)
community
resiliencecomm_recov level of recovery of the community
a Fitting a three level model requires two random-effect equations one for level three (country) and one for level two (community) with i = 1 nvc 1047297rst level of
observation (households) nested within k = 1 8 s level cluster (community) nested within j = 1 4 third level cluster (country)
162 C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
community level in the same way than the QoL indices that is by
averaging the scores obtained at the individual household level)
The best correlation was obtained with the QoL index of social
capital in time of crisis (R 2= 077 F = 0004) see Fig 6- suggesting
that communities with higher social capital in time of crisis are
also characterized by higher level of resilience
5 Discussion
Resilience has been increasingly recognized as a potentially
useful concept to help practitioners academics and policy-makers
better understand the links between shocks response and longer-
term development outcomes (Constas et al 2014a Beacuteneacute et al
2014) Incorporating resilience alongside vulnerability analysis can
contribute an essential element to societal ability to better prepare
for future shocks and stressors This paper argues that improving
our understanding of what contributes to or constitutes peoplersquos
resilience requires not only the development and
1047297eld-testing of
robust and measurable indices (Beacuteneacute 2013 Constas et al 2014b)
but also a better insight into the social factors including
knowledge perceptions and motivations- that in1047298uence and affect
individual and collective capacity to respond to shocks and
stressors
Our analysis conducted in eight 1047297shery-dependent communi-
ties from Fiji Ghana Sri Lanka and Vietnam reveals a series of
notable results in relation to these questions In considering these
outcomes it is important to 1047297rst take stock of potential limitations
pitfalls or biases in the study methodology Given the nature of the
1047297ndings two potential issues require further consideration First is
the question of how representative our sampling methodology
was It could be argued for instance that the observed low adoption
rates of non-1047297shery strategiesndash and in particular the low score of
the
lsquoexiting the
1047297sheryrsquo was driven by our sampling method
underrepresenting these groups as those who had effectively left
the 1047297shery were not included in the sample
The FGDs that preceded the household survey speci1047297cally
addressed this issue In Sri Lanka for instance the opening question
prompted participants (both men and women) to discuss whether
ldquo1047297shers in their community had ever left 1047297sheries due to their
inability to cope with adverse eventsrdquo The answer was that it
generally does not happen with the notable exception of someyoung
1047297shers who attempted to migrate to Australia through
illegal means If it occurred exiting the 1047297shery was said to be
temporary ldquothey may leave the village or 1047297shing but will come
back when the situation is favourablerdquo In Vietnam the sampling
was speci1047297cally designed to cover both
1047297shers and ex-1047297shers in
proportions represented in the community As a result 9 ex-1047297shers
were included in the sample Overall therefore although we were
unable to conceive of a completely representative sampling design
(in the statistical sense) the parallel information that was collected
in the FGDs and the individual households converge to suggest that
exiting the
1047297shery was not an option envisaged by the members of
these different communities and consequently that our sampling
was not too severely biased
0
2
4
6
8
10
12
14
16
-05 05 15 25
C o m m u n i t y l e v e l r e s i l i
e n c e i n d e x
Community level social capital in me of crisis
Fiji
Ghana
Sri Lanka
Vietnam
Fig 6 Correlation between social capital in time of crisis and resilience index
across the eight communities The straight line represents the linear relation
(R 2 = 077 F = 0004) and the bars are 95 con1047297dence intervals for each community
Random-effects parameters St Dev Std Err [95 Conf Interval]
country level
index_incom 043 024 0146 1266
index_livelih 051 027 0175 1464
index_housing 013 013 0018 0962
index_soc 039 024 0119 1303
index_soc_cris
078
038
0300
2009index_educ 015 013 0028 0834
const 090 067 0209 3861
community level
const 032 026 0066 1534
residuals 277 008 2617 2923
LR test vs linear regression chi2(7) = 3916 Prob gt chi2= 0000
p
lt 5
p
lt
1 p lt 1ma Fitting a three level model requires two random-effect equations one for level three (country) and one for level two (community) with i = 1 nvc 1047297rst level of
observation
(households)
nested
within
k
=
1
8
second
level
cluster
(community)
nested
within
j
=
1
4
third
level
cluster
(country)b The likelihood-ratio (LR) test comparing the nested mixed-effects model with the corresponding 1047297xed effect model con1047297rms the appropriate use of the mixed effect
model (chi2(7) = 3916 Prob gt chi2= 0000) and the Wald test con1047297rms that the independent variables are valid predictors (Wald chi2(45) = 59414 Prob gt chi2= 0000) A
speci1047297cation test performed on the 1047297xed effect model using a Pregibonrsquos goodness-of-link test shows good results (t = 077 P gt |t| = 0439)
c The dummy variables sev_event3 cat_event2 predict2 and comm_recov3 were omitted from the 1047297xed effect component for estimation purpose
Table 7 (Continued)
164 C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
The second potential limitation in our methodology relates to
the way the level of resilience of the households was assessed
While psychometric measurements are reliable and their results
replicable and testable when correctly implemented (Vigderhous
1977) one could fear that their use in the speci1047297c case of resilience
measurement could be subject to the effect of adaptive preference
that is the deliberate or re1047298exive process by which people adjust
their expectations and aspirations when trying to cope with
deterioration in living conditions (see eg Nussbaum 2001 Teschl
and Comim 2005) In our case this means that households
undergoing a degree of adaptive preference could have over-
estimated their ability to recover Although this risk is present we
tried to mitigate (or to reduce) it by introducing a qualifying
element in each of the coded answers of the resilience question-
naire so that respondents would have to associate the
1047297rst part of
their answer ldquoI have fully recoveredrdquo with a particular lsquoframe of
reference or quali1047297er (eg ldquoand it was not too dif 1047297cultrdquo) This frame
determined how they comprehend the questions being asked and
reduced the risk of the respondent simply relying on emotional
elements to answer these questions
Keeping in mind these potential limitations we now turn to
what we consider the most notable results of this research First is
the
lsquocumulative and continuous effect of shocks and stressors
whereby the impacts and disturbance of sequential shocksstressors and trends during the last 1047297ve years combine and
coalesce to create a constant non-stop stress We saw that the
nature and the source of events that were identi1047297ed by the
respondents in the four countries are all highly varied and
composite and reveal no speci1047297c clear pattern The events are a
combination of idiosyncratic and covariant sudden shocks and
long-term continuous trends Some are predictable while others
are totally unexpected All affect households simultaneously and
on an almost continuous basis The data suggests in particular that
on average households are hit by a new event every 16 months
This result calls into questions the framework generally used to
conduct shock or vulnerability assessment Often the approach has
been to disaggregate the problems people face and focus on single
threats such as eg 1047298ood or increase in food prices in order todevelop a clearer understanding of the impact of these particular
shocks and the ways people respond to them This approach has
been challenged however by a growing number of scholars who
argue that the reality households face on a daily basis is not linear
and mono-dimensional (OrsquoBrien and Leichenko 2000 Eriksen and
Silva 2009 Quinn et al 2011 McGregor 2011) Instead they argue
risks and vulnerability are often the product of multiple stressors
(Turner et al 2003 OrsquoBrien et al 2009) where social economic
political and biophysical factors interact combine and reinforce
each other to create a complex and dynamic multi-stressor multi-
shock environment (Reid and Vogel 2006 Adger 2006) Our
results corroborate this new interpretation
In line with this our analysis also shows that most households
engage in a suite of responses to a given shock On average
households adopted more than 4 types of responses to a particular
event This last result does not simply imply a rethinking of the way
shock or vulnerability assessments are conceptualized and
conducted see eg Turner et al (2003) or Leichenko and OrsquoBrien
(2008) It also demonstrates that the mental model (shock
gt response gt recovery) which is widely accepted in the
resilience literature is too simplistic and possibly misleading in
the sense that a state of (full) recovery may not exist This is at least
what was observed for the households included in our research
these households did not seem to have the chance or the time to
fully recover from one particular event before being affected by the
next Instead they were caught in what we could characterize as ldquoaconstant state of incomplete recoveringrdquo from new shocks and
stressors as illustrated in Fig 7
The next entry point in this discussion is wealth Our mixed
effect model (Table 7) shows that wealth was positively correlated
with household resilience Wealth has been identi1047297ed in the
literature as a key factor in strengthening the resilience of
households (Prowse and Scott 2008 WFP 2013) Analysis of
rural Ethiopian households hit by drought for instance showed that
while better-off households could sell livestock to smooth
consumption the poorer often tried to hold on to their livestock
at the expense of food consumption to preserve their options for
rebuilding herds The same study also shows that in the aftermath
of the hurricane Mitch in Honduras the relatively wealthy
households were able to rebuild their lost assets faster than thepoorest households for whom the effects of the hurricane were of
longer duration and felt much more acutely (Carter et al 2007) In
Fig 7 Left Current conceptualisation of resilience shock gt response gt recovery as presented in the literature [here redrawn from Carter et al 2007] Right actual
situation where the multi-stressor multi-shock environment induces that households are in a trajectory of continual and incomplete recovery Not represented here are the
multi-response
strategies
put
in
place
by
households
to
respond
to
these
adverse
events
C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170 165
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
disaster resilience National Disaster Resilience Roundtable Report 20September 2012 Melbourne Australia 36 p
Adger NW Dessai S Goulden M Hulme M Lorenzoni I Nelson DR Naess LO Wolf J Wreford A 2009 Are there social limits to adaptation to climatechange
Clim
Change
93
335ndash354Adger WN 2003 Social capital collective action and adaptation to climate
change Econ Geogr 79 (4) 387ndash404Adger WN 2006 Vulnerability Glob Environ Change 16 268ndash281Aldrich D 2010 Fixing recovery social capital in post-Crisis resilience J Homeland
Secur 6 1ndash10Ayers
J
Forsyth
T
2009
Community-based
adaptation
to
climate
changestrengthening resilience through development Environment 51 23ndash31
Beacuteneacute C Tew1047297k A 2001 Fishing effort allocation and 1047297shermenrsquos decision-makingprocess in a multi-species small-scale 1047297shery analysis of the conch and lobster1047297shery in Turks and Caicos Islands Hum Ecol 29 (2) 157ndash186
Beacuteneacute
C
Evans
L
Mills
D
Ovie
S
Raji
A
Ta1047297da
A
Kodio
A
Sinaba
F
Morand
PLemoalle J Andrew N 2011 Testing resilience thinking in a poverty contextexperience from the Niger river basin Glob Environ Change 21 (4) 1173ndash1184
Beacuteneacute C Godfrey-Wood R Newsham A Davies M2012 Resilience new utopia ornew tyranny
ndash Re1047298ection about the potentials and limits of the concept of
resilience
in
relation
to
vulnerability
reduction
programmes
IDS
Working
Paperno 405 Institute of Development Studies Brighton 61 p
Beacuteneacute C Newsham A Davies M Ulrichs M Godfrey-Wood R 2014 Resiliencepoverty and development J Int Dev 26 598ndash623
Beacuteneacute C Waid J Jackson-deGraffenried M Begum A Chowdhury M Skarin VRahman A Islam N Mamnun N Mainuddin K Shah MA 2015a Impact of climate-related
shocks
and
stresses
on
nutrition
and
food
security
in
ruralBangladesh Dhaka World Food Programme 119 p
Beacuteneacute C Frankenberger T Nelson S 2015b Design monitoring and evaluation of resilience interventions conceptual and empirical considerations IDS WorkingPaper no459 Institute of Development Studies 23 p
Beacuteneacute
C
2013
Towards
a
quanti1047297able
measure
of
resilience
IDS
Working
Paper
434Institute of Development Studies Brighton 27 p
Bandura A 1977 Self-ef 1047297cacy toward a unifying theory of behavioral changePsychol Rev 84 191ndash215
Baulch R Hoddinott J 2000 Economic mobility and poverty dynamics indeveloping countries J Dev Stud 36 (6) 1ndash23
Belhabib
D
Sumaila
UR
Pauly
D
2015
Feeding
the
poor
contribution
of
WestAfrican 1047297sheries to employment and food security Ocean Coast Manage 11172ndash81
Berkes F Folke C 1998 Linking social and ecological systems for resilience andsustainability In Berkes F Folke C (Eds) Linking Social and EcologicalSystems Management Practices and Social Mechanisms for Building ResilienceCambridge University Press Cambridge pp 1ndash25
Bernier Q Meinzen-Dick R 2014 Resilience and social capital Building Resiliencefor Food and Nutrition Security Conference Paper No 4 International FoodPolicy Research Institute Washington DC 26 p
Bhattamishra R Barrett C 2010 Community-Based risk managementarrangements a review World Dev 38 (7) 923ndash932
Boarini R Kolev A McGregor JA 2014 Measuring well-being and progress incountries at different stages of development towards a more universalconceptual framework OECD Working Paper No 235 Organisation forEconomic Co-operation and Development Development Center
ndash Better Life
Initiative Paris 59 p
Boyd E Osbahr H Ericksen P Tompkins E Carmen Lemos M Miller F 2008Resilience and
lsquoclimatizingrsquo development examples and policy implicationsDevelopment 51 390ndash396
Cam1047297eld
L
McGregor
JA
2005
Resilience
and
wellbeing
in
developing
countriesIn Ungar M (Ed) Handbook for Working with Children and Youth Pathwaysto Resilience Across Cultures and Contexts Sage Publications Thousand OaksCA
Cam1047297eld
L
Ruta
D
2007
Translation
is
not
enough
using
the
Global
PersonGenerated Index (GPGI) to assess individual quality of life in BangladeshThailand and Ethiopia Qual Life 16 (6) 1039ndash1051
Carter M Little P Mogues T Negatu W 2007 Poverty traps and natural disastersin Ethiopia and Honduras World Dev 35 (5) 835ndash856
Cleaver
F
2005
The
inequality
of
social
capital
and
the
reproduction
of
chronicpoverty World Dev 33 (6) 893ndash906
Constas M Frankenberger T Hoddinott J 2014a Resilience measurementprinciples toward an agenda for measurement design Resilience MeasurementTechnical Working Group Technical Series No 1 Food Security informationNetwork Rome
Constas MT Frankenberger J Hoddinott N Mock D Romano C Beacuteneacute DMaxwell 2014b A common analytical model for resilience measurementcausal framework and methodological options Food Security InformationNetwork (FSIN) Technical Series No 2 World Food Programme Rome
Coulthard S 2011 More than just access to 1047297sh the pros and cons of 1047297sherparticipation
in
a
customary
marine
tenure
(Padu)
system
under
pressure
MarPolicy 35 405ndash412
DFID 2011 De1047297ning Disaster Resilience A DFID Approach Paper Department forInternational Development London pp 20
Dercon S Hoddinott J Woldehanna T 2005 Shocks and consumption in 15ethiopian
villages
1999ndash2004
J
Afr
Econ
14
(4)
559ndash585Dercon S 1996 Risk crop choice and savings evidence from Tanzania Econ Dev
Cult Change 44 (3) 485ndash513Duit A Galaz V Eckerberg K 2010 Governance complexity and resilience Glob
Environ Change 20 (3) 363ndash368Eriksen
SEH
Silva
JA
2009
The
vulnerability
context
of
a
savannah
area
inMozambique household drought coping strategies and responses to economicchange Environ Sci Policy 12 (1) 33ndash52
Fafchamps M Lund S 2003 Risk-Sharing networks in rural Philippines J DevEcon 71 (2) 261ndash287
Frankenberger T Nelson S 2013 Background Paper for the Expert Consultation onResilience
Measurement
for
Food
Security
TANGO
International
Rome
Foodand Agricultural Organization and World Food Program
Heltberg R Siegel PS Jorgensen SL 2009 Addressing human vulnerability toclimate change towards a
lsquono-regretsrsquo approach Glob Environ Change 19 89ndash99
Hoddinott
J
Dercon
S
Krishnan
P
2009
Networks
and
informal
mutual
supportin 15 ethiopian villages a description In Kirsten JF Dorward AR Poulton CVink N (Eds) Institutional Economics Perspectives on African AgriculturalDevelopment International Food Policy Research Institute Washington DC pp273ndash286
Hoddinott
J
2006
Shocks
and
their
consequences
across
and
within
households
inRural Zimbabwe J Dev Stud 42 (2) 301ndash321
Intergovernmental Panel on Climate Change (IPCC) 2012 In Field CB Barros VStocker TF Qin D Dokken DJ Ebi KL Mastrandrea MD Mach KJPlattner G-K Allen SK Tignor MMidgley PM (Eds) Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation A SpecialReport of Working Groups I and II of the Intergovernmental Panel on ClimateChange Cambridge University Press Cambridge UK
Jackson T 2005 Motivating sustainable consumptionmdasha review of evidence onconsumer behaviour and behavioural change A Report to the Sustainable
Event type (Vietnam) Reduce
expenditures
Borrow
money
Reduce
Food
Change
1047297shing
strategy
Get
support
Increase
1047297shing
effort
Diversi1047297cation Seek new
collaboration
Migration Exit the
1047297shery
Sell
assets
Total
Others (aggregated) 4 7 4 6 3 0 1 3 0 0 2 30
Erosion 2 4 2 1 6 2 2 2 3 1 25
Catch reduced
suddenly
8 4 6 7 1 2 4 2 34
Gears lost 10 18 6 5 1 2 1 43
Cold wind prolongs 15 7 11 3 1 7 2 46
Typhoon
12
11
10
2
4
2
3
5
4
1
1
55
Illness
11 14
6
2
11
2
2
4
1
1
2
56Food price increase 20 17 19 2 8 5 1 72
Input price increase
continuously
47 39 33 21 40 5 6 16 1 208
Big boats compete
ground and catch
54 39 32 40 9 19 11 15 8 3 2 232
Catch
reduced
continuously
102
70
80
63
22
51
51
25
23
17
6
510
Total 285 230 209 152 105 91 87 75 39 23 15 1311
C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170 169
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
Development Research Network Centre for Environmental StrategiesUniversity of Surrey
Jones L Boyd E 2011 Exploring social barriers to adaptation insights fromWestern Nepal Glob Environ Change 21 (4) 1262ndash1274
Kallstrom HN Ljung M 2005 Social sustainability and collaborative learningAmbio 34 376ndash382
Kelty R Kelty R 2011 Human dimensions of a 1047297shery at a crossroads resourcevaluation identity and way of life in a seasonal 1047297shing community Soc NatResour
24
(4)
334ndash348Klein RJT Nicholls RJ Thomalla F 2003 Resilience to natural hazards how
useful is this concept Environ Hazards 5 35ndash45
Krosnick
JA
Fabrigar
LR
1997
Designing
rating
scales
for
effective
measurementin surveys In Lyberg L Biemer P Collins M de Leeuw E Dippo C SchwarzN
Trewin
D
(Eds)
Survey
Measurement
and
Process
Quality
John
Wiley
andSons Inc New York NY pp 141ndash164
Leichenko R OrsquoBrien K 2008 Environmental Change and Globalization DoubleExposures Oxford University Press New York
Marschke M Berkes F 2006 Exploring Strategies that build livelihood resiliencea case from Cambodia Ecol Soc 11 (1) httpwwwecologyandsocietyorgvol11iss1art42
McGregor JA Cam1047297eld L Woodcock A 2009 Needs wants and goals wellbeingquality
of
life
and
public
policy
Appl
Res
Qual
Life
4
135ndash154McGregor JA 1994 Village credit and the reproduction of poverty in rural
Bangladesh In Acheson J (Ed) Economic Anthropology and the NewInstitutional Economics University Press of AmericaSociety for EconomicAnthropology Washington pp 261ndash281 (Chapter)
McGregor
JA
2011
Reimagining
development
through
the
crisis
watch
initiative
IDS Bull 42 (5) 17ndash23McLaughlin P Dietz T 2007 Structureagency and environment toward an
integrated perspective on vulnerability Glob Environ Change 39 (4) 99ndash111Meyer MA 2013 Social capital and resilience in the context of disaster social
capital
and
collective
ef 1047297cacy
for
disaster
resilience
connecting
individualswith communities and vulnerability with resilience in hurricane-pronecommunities in Florida PhD Dissertation Department of sociology Coloradostate University Fort Collins Colorado (311 p)
Mills DJ Adhuri D Phillips M Ravikumar B Padiyar AP 2011 Shocks recoverytrajectories and resilience among aquaculture-dependent households in post-tsunami
Aceh
Indonesia
Local
Environ
Int
J
Justice
Sustain
16
(5)
425ndash444Morduch J 1995 Income smoothing and consumption smoothing J Econ
Perspect 9 (3) 103ndash114Morris S Carletto C Hoddinott J Christiaensen L 2000 J Epidemiol Commun
Health 54 381ndash387Myers
RA
Worm
B
2003
Rapid
worldwide
depletion
of
predatory 1047297sh
communities Nature 423 280ndash283Nakagawa Y Shaw R 2004 Social capital a missing link to disaster recovery Int J
Mass
Emerg
Disasters
22
(1)
5ndash
34Nussbaum MC 2001 Adaptive preferences and womenrsquos options Econ Philos 1767ndash88
Oslashstergaard N Reenberg A 2010 Cultural barriers to climate change adaptation acase study from Northern Burkina Faso Glob Environ Change 20 (1) 142ndash152
OrsquoBrien K Leichenko R 2000 Double exposure assessing the impacts of climatechange within the context of economic globalization Glob Environ Change 10221ndash232
OrsquoBrien K Eriksen S Sygna L Naess LO 2006 Questioning complacencyclimate change impacts vulnerability and adaptation in Norway AMBIO JHum Environ 35 (2) 50ndash56
OrsquoBrien K Quilan T Ziervogel G 2009 Vulnerability interventions in the contextof multiple stressors lessons from the Southern Africa vulnerability initiative(SAVI) Environ Sci Policy 12 23ndash32
OrsquoRiordan T Jordan A 1999 Institutions climate change and cultural theorytowards a common analytical framework Glob Environ Change 9 (2) 81ndash93
Pain A Levine S 2012 A conceptual analysis of livelihoods and resilienceaddressing the
lsquoinsecurity of agency HPG Working Paper OverseasDevelopment Institute Humanitarian Policy Group London
Pauly D Christensen V Dalsgaard Froese JR Torres F 1998 Fishing downmarine food webs Science 279 (5352) 860ndash863
Pelling M Manuel-Navarrete D 2011 From resilience to transformation theadaptive cycle in two Mexican urban centersEcol Soc 16 (2)11 (online) httpwwwecologyandsocietyorgvol16iss2art11
Prowse
M
Scott
L
2008
Assets
and
adaptation
an
emerging
debate
IDS
Bull
39(4) 42ndash52
Putzel J 1997 Accounting for the lsquodark sidersquo of social capital reading Robert
Putnam
on
democracy
J
Int
Dev
9
(7)
939ndash949
Quinn CH Ziervogel G Taylor A Takama T Thomalla F 2011 Coping withmultiple
stresses
in
rural
South
Africa
Ecol
Soc
16
(3)
doihttpdxdoiorg105751ES-04216-160302
Reid P Vogel C 2006 Living and responding to multiple stressors in South Africamdashglimpses from KwaZulu-Natal Glob Environ Change 16 (2) 195ndash206
Roncoli C Ingram K Kirshen P 2001 The costs and risks of coping with droughtlivelihood
impacts
and
farmersrsquo
responses
in
Burkina
Faso
Clim
Res
19
119ndash132
Schwarz AM Beacuteneacute C Bennett G Boso D Hilly Z Paul C Posala R Sibiti SAndrew N 2011 Vulnerability and resilience of rural remote communities toshocks and global changes empirical analysis from the Solomon Islands GlobEnviron Change 21 1128ndash1140
Sinha
S
Lipton
M
Yaqub
S
2002
Poverty
and
damaging 1047298uctuations
how
dothey relate J Asian Afr Stud 37 (2) 186ndash243
Tansey J OrsquoRiordan T 1999 Cultural theory and risk a review Health Risk Soc 171ndash90
Teschl M Comim F 2005 Adaptive preferences and capabilities somepreliminary
conceptual
explorations
Rev
Soc
Econ
63
(2)
229ndash247
Trimble M Johnson D 2013 Artisanal 1047297shing as an undesirable way of life Theimplications for governance of 1047297shersrsquo wellbeing aspirations in coastal Uruguayand southeastern Brazil Mar Policy 37 37ndash44
Turner BL Kasperson RE Matson P McCarthy JJ Corell RW Christensen LEckley
N
Kasperson
JX
Luers
A
Martello
ML
Polsky
C
Pulsipher
ASchiller A 2003 A framework for vulnerability analysis in sustainabilityscience Proc Natl Acad Sci 100 (14) 8074ndash8079
Vigderhous G 1977 The level of measurement and
lsquoPermissiblersquo statistical analysisin social research Pac Sociol Rev 20 (1) 61ndash72
WFP 2013 Building Resilience Through Asset Creation Resilience and PreventionUnit
Policy
Programme
and
Innovation
Division
World
Food
Program
Rome(23 p)
Walker B Carpenter S Anderies J Abel N Cumming GS Janssen M Lebel LN J Peterson GD Pritchard R 2002 Resilience management in social-ecological systems a working hypothesis for a participatory approach ConservEcol
6
(1)
14Weber EU 2010 What shapes perceptions of climate change Clim Change 1 (3)
332ndash342
Wolf
J
Adger
WN
Lorenzoni
I
Abrahamson
V
Raine
R
2010
Social
capitalindividual responses to heat waves and climate change adaptation an empiricalstudy
of
two
UK
cities
Glob
Environ
Change
20
44ndash52Wood G 2003 Staying secure staying poor the Faustian bargain World Dev 31
(3) 455ndash471World Bank 2011 Building Resilience and Opportunities World Bankrsquos Social
Protection and Labour Strategy 2012ndash2022 World Bank Washington DCYamano T Alderman H Christiaensen L 2003 Child Growth Shocks and Food
Aid in Rural Ethiopia World Bank Washington DCZimmerman F Carter M 2003 Asset smoothing consumption smoothing and the
reproduction of inequality under risk and subsistence constraints J Dev Econ71 233ndash260
von Grebmer K Headey D Beacuteneacute C Haddad L et al 2013 Global Hunger IndexThe Challenge of Hunger Building Resilience to Achieve Food and NutritionSecurity Welthungerhilfe International Food Policy Research Institute andConcern Worldwide Bonn Washington DC and Dublin
170 C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
Resilience outcomes were explored using psychometric tech-
niques where households were asked to self-assess the degree of
recovery they managed to achieve for each of the adverse events
they had experienced in the past (see details in Table 2) The
answers provided by the respondents to the 1047297rst two questions of
the resilience analysis (self-recovery from past event and self-
recovery compared to the rest of the community) were used to
create a resilience index (RI) computed as the product of the two
scores As a result of the calculation process RI is an integer varying
between 1 and 30 where low values indicate low level of resilienceto a speci1047297c event while higher values indicate higher levels of
resilience
We then used this resilience index to explore the last remaining
working hypothesis of this research that is that
lsquosocial capital is
importantrsquo- ie the (intuitive) idea that households or communi-
ties characterized by higher level of social capital are able to draw
on social capital to help themselves (and others) in the aftermath
of an adverse event To analyse the resilience outcomes and explore
in particular this last hypothesis a three-level mixed effect linear
model was run where the resilience index was tested against a
series of 1047297xed and random factors used as independent explana-
tory variables Because the communities are nested within the
countries a three-level (hierarchical) model was
1047297tted with
random intercepts at both country and community-within-
country levels Random coef 1047297cients were also accounted for at
the country level on the Quality of Life (QoL) factors to re1047298ect
country speci1047297c effects More speci1047297cally the model was of the
form
RI vc frac14 b0 thorn b1Shockvc thorn b2Respvc thorn b3QoLvc thorn b4HH vc thorn g 1W c thorn g 2 Z vc thorn
evc
where the subscripts v and c hold for village (community) and
country respectively Shockvc is the covariate matrix for the
1047297xed
effect
b1 of the impacts of event e on individual household Respvc
is the covariate matrix for the 1047297xed effect b2 of the responses put in
places by the household QoLe is the covariate matrix for the
1047297xed
effect b3 of the Quality of Life scores recorded for each household
HH e is the matrix of variables and dummies controlling for
household characteristics W c is the covariate matrix for the cluster
random effect at the country level and Z vc is the covariate matrix
for the cluster random effect at the community level The details of
the different categories of variables included in the model are
provided in Table 6
Results of the model estimations including details of both
1047297xed and random effect speci1047297cations and diagnostic checking-
are presented in Table 7 The model highlights a series of important
1047297ndings First the degree of severity of the shock and the
disruptive impact on income are the twoshock variables that have
0
10
20
30
40
50
60
70
80
90
F o o d
E x p e n s e s
M o n e y
A s s e s t
S u p p o r t
C o l l a b o r a o n
D i v e r s i fi c a o n
M i g r a o n
E x i t
C h a n g e
I n c r e a s e
P e r c e n t a g e o f h o u s e h o l d s ( )
Response typology (Vietnam)
Boom 40
Top 40
0
01
02
03
04
05
06
07
F o o d
E x p e n s e s
M o n e y
A s s e t s
S u p p o r t
C o l l a b o r a o n
D i v e r s i fi c a o n
M i g r a o n
E x i t
C h a n g e
I n c r e a s e
P e r c e n t a g e o f h o u s e h o l d s ( )
Response typology (Fiji)Boom 40
Top 40
Fig 5 Comparative analysis of the responses adopted by the bottom (poorest) and top (wealthiest) 40 of the households when affected by the same event illustration
from Vietnam and Fiji Code of the responses
ldquoFoodrdquo = Reduce food consumption
ldquoExpensesrdquo = Reduce family general expenses
ldquoMoneyrdquo = Borrow money
ldquoAssetsrdquo = Sell
family assets
ldquoSupportrdquo= Seek for support from friends and peers
ldquoCollaborationrdquo= Develop new collaboration within the community
ldquoDiversi1047297cationrdquo = Invest in non-
1047297shery activities ldquoMigrationrdquo = Temporary permanently migration one or several members of the family ldquoExitrdquo = Exit the 1047297shery start a new joblivelihoodldquoChangerdquo = Change 1047297shing strategies
ldquoIncreaserdquo = Increase 1047297shing effort
160 C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
The type of responses adopted by households was included in
the model to test whether the level of resilience of households is
effectively in1047298uenced by those responses Amongst the 11 types of
responses tested three have statistically signi1047297cant signs engag-
ing
in
new
collaboration
(negative
sign
P
=
0001)
increasing1047297shing effort (positive P lt 00001) and quitting the
1047297shery
(negative P = 0047) The negative correlation found between
household resilience and the strategy that consists of forming new
collaboration may be dif 1047297cult to interpret as it can re1047298ect many
highly contextual factors The two others responses and the signs
of their correlations (one negative sign for leaving the sector and
one positive sign for increasing 1047297shing effort) are initially
disturbing but eventually not too surprising Disturbing
1047297rst
because this
1047297nding does not lead to the type of long-term
behaviours that appeal to policy makers and 1047297shery managers On
the contrary they would rather see 1047297shing effort reductions and
exit strategies more often adopted by
1047297shers in particular in the
context of the current world
1047297shery crisis Not surprising however
because this result is in line with what one could expect from
1047297sherfolks after an adverse event in the face of a long-term stress
(such
as
the
drop
in
income
following
a
continuous
decline
in
1047297shcatch) or a sudden need for cashrevenues (as a consequence of
eg destruction of 1047297shing gear induced by bad weather or the
need to pay health bills)
1047297shers are often observed to alter their
1047297shing activities to make up for these events usually by changing
adjusting their 1047297shing strategy (eg switching between targeted
species andor
1047297shing gear) or increasing their
1047297shing effort (eg
investing in more ef 1047297cient
1047297shing gear increasing the quantity of
gear used or increasing the number of days at sea) in an attempt to
generate more cash In that context it is not surprising that the
majority of 1047297shing households interviewed in this research
consider that their ability to
lsquobounce back following an adverse
event was enhanced when they increase their 1047297shing effort
Additionally given what we know about their strong sense of
identity
(Kelty
and
Kelty
2011
Trimble
and
Johnson
2013) but
alsothe importance of peer-pressure and reputation (see eg Beacuteneacute and
Tew1047297k 2001) quitting the 1047297shery would certainly be perceived by
many 1047297shers as a failure thus the negative correlation between
(perceived) resilience and leaving the sector
The next category of variables which was investigated through
the model was the Quality of Life indicators (see Table 3 for a
recall) A reasonable hypothesis although not explicitly formu-
lated in the
lsquoworking hypotheses section above- is that some of
these QoL indices may have a positive effect on the ability of
households to handle and recover from adverse events One can
indeed assume that households satis1047297ed in many of the
dimensions of wellbeing which they considers important (such
as say access to health services or to public infrastructure) may
feel better equipped to reactrespond to any particular event than
Table 5
Top comparison of propensities to adopt particular types of responses for households characterized by high (N = 224) and low (N = 235) subjective resilience Bottom
comparison of the two same groups in terms of asset levels education and age of the household head
Responses subjective
resilience
level
Mean [95 Conf
Interval]
test resulta
Coping strategies High 198 1840 2136 t = 43037 Pr(|T| gt |
t|) = 0000
Low 245 2311 2596
Social-relation-based strategies High 083 0738 0927 t = 05187 Pr(|T| gt |
t|) = 0604
Low 086 0787 0943
Fishing-related strategies High 083 0732 0935 t = 03267 Pr(|T| gt |
t|)
=
0744
Low 081 0715 0906
Non-1047297shery
strategies
High
067
0559
0794
t
=
35599
Pr(|T|
gt
|
t|) = 0000
Low 042 0341 0502
Household characteristics
Asset High 768 7218 8157 t = 08882 Pr(|T| gt |
t|) = 0374
Low 739 6938 7848
Education High 796 7338 8599 t = 10186 Pr(|T| gt |
t|)
=
0308
Low 750 6857 8147
Age High 4688 45377 48391 t = 01332 Pr(|T| gt |
t|) = 0894
Low 4702 45570 48482
p
lt 5
p
lt 1
p
lt 1
a mean difference unpaired t -test Ho Diff = 0 Ha diff 6frac14 0
C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170 161
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
diversif non 1047297sher diversi1047297cation dummy 1 = yes
exit_1047297sh exit the 1047297shery sector dummy 1 = yes
migrat migrate dummy 1 = yes
quality of life indices
index_incom
income
index
ordinal
variable
coded
[-6
+6]
ndash6
=
very
poor
+6
=
very
strong
index_livelih livelihood index ordinal variable coded [-6 +6] ndash6 = very poor +6 = very strongindex_housing housing and infrastructure index ordinal variable coded [-6 +6] ndash6 = very poor +6 = very strong
index_educ education index ordinal variable coded [-6 +6]
ndash6 = very poor +6 = very strong
index_soc social capital index ordinal variable coded [-6 +6]
ndash6 = very poor +6 = very strong
index_health health index ordinal variable coded [-6 +6] ndash6 = very poor +6 = very strong
ind_emp empowerment index ordinal variable coded [-6 +6]
ndash6 = very poor +6 = very strong
index_soc_cris social capital index in time of crisis
ndash6 = very poor +6 = very strong
index_emp_cris empowerment index in time of crisis
ndash6 = very poor +6 = very strong
index_spirit index of spirituality
ordinal variable coded [-6 +6]
ndash6 = very poor +6 = very strong
household characteristics
HH head sex sex of household head dummy 1 = female
HH
head
age
age
of
household
head
age
in
years
HH head educ level of education of the household head 0 = no education 20 = post-graduate level
HH size size of household number of members (not adjusted for age)
log_asset household assets (log-transformed) value of household assets (proxy for wealth level)
community
resiliencecomm_recov level of recovery of the community
a Fitting a three level model requires two random-effect equations one for level three (country) and one for level two (community) with i = 1 nvc 1047297rst level of
observation (households) nested within k = 1 8 s level cluster (community) nested within j = 1 4 third level cluster (country)
162 C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
community level in the same way than the QoL indices that is by
averaging the scores obtained at the individual household level)
The best correlation was obtained with the QoL index of social
capital in time of crisis (R 2= 077 F = 0004) see Fig 6- suggesting
that communities with higher social capital in time of crisis are
also characterized by higher level of resilience
5 Discussion
Resilience has been increasingly recognized as a potentially
useful concept to help practitioners academics and policy-makers
better understand the links between shocks response and longer-
term development outcomes (Constas et al 2014a Beacuteneacute et al
2014) Incorporating resilience alongside vulnerability analysis can
contribute an essential element to societal ability to better prepare
for future shocks and stressors This paper argues that improving
our understanding of what contributes to or constitutes peoplersquos
resilience requires not only the development and
1047297eld-testing of
robust and measurable indices (Beacuteneacute 2013 Constas et al 2014b)
but also a better insight into the social factors including
knowledge perceptions and motivations- that in1047298uence and affect
individual and collective capacity to respond to shocks and
stressors
Our analysis conducted in eight 1047297shery-dependent communi-
ties from Fiji Ghana Sri Lanka and Vietnam reveals a series of
notable results in relation to these questions In considering these
outcomes it is important to 1047297rst take stock of potential limitations
pitfalls or biases in the study methodology Given the nature of the
1047297ndings two potential issues require further consideration First is
the question of how representative our sampling methodology
was It could be argued for instance that the observed low adoption
rates of non-1047297shery strategiesndash and in particular the low score of
the
lsquoexiting the
1047297sheryrsquo was driven by our sampling method
underrepresenting these groups as those who had effectively left
the 1047297shery were not included in the sample
The FGDs that preceded the household survey speci1047297cally
addressed this issue In Sri Lanka for instance the opening question
prompted participants (both men and women) to discuss whether
ldquo1047297shers in their community had ever left 1047297sheries due to their
inability to cope with adverse eventsrdquo The answer was that it
generally does not happen with the notable exception of someyoung
1047297shers who attempted to migrate to Australia through
illegal means If it occurred exiting the 1047297shery was said to be
temporary ldquothey may leave the village or 1047297shing but will come
back when the situation is favourablerdquo In Vietnam the sampling
was speci1047297cally designed to cover both
1047297shers and ex-1047297shers in
proportions represented in the community As a result 9 ex-1047297shers
were included in the sample Overall therefore although we were
unable to conceive of a completely representative sampling design
(in the statistical sense) the parallel information that was collected
in the FGDs and the individual households converge to suggest that
exiting the
1047297shery was not an option envisaged by the members of
these different communities and consequently that our sampling
was not too severely biased
0
2
4
6
8
10
12
14
16
-05 05 15 25
C o m m u n i t y l e v e l r e s i l i
e n c e i n d e x
Community level social capital in me of crisis
Fiji
Ghana
Sri Lanka
Vietnam
Fig 6 Correlation between social capital in time of crisis and resilience index
across the eight communities The straight line represents the linear relation
(R 2 = 077 F = 0004) and the bars are 95 con1047297dence intervals for each community
Random-effects parameters St Dev Std Err [95 Conf Interval]
country level
index_incom 043 024 0146 1266
index_livelih 051 027 0175 1464
index_housing 013 013 0018 0962
index_soc 039 024 0119 1303
index_soc_cris
078
038
0300
2009index_educ 015 013 0028 0834
const 090 067 0209 3861
community level
const 032 026 0066 1534
residuals 277 008 2617 2923
LR test vs linear regression chi2(7) = 3916 Prob gt chi2= 0000
p
lt 5
p
lt
1 p lt 1ma Fitting a three level model requires two random-effect equations one for level three (country) and one for level two (community) with i = 1 nvc 1047297rst level of
observation
(households)
nested
within
k
=
1
8
second
level
cluster
(community)
nested
within
j
=
1
4
third
level
cluster
(country)b The likelihood-ratio (LR) test comparing the nested mixed-effects model with the corresponding 1047297xed effect model con1047297rms the appropriate use of the mixed effect
model (chi2(7) = 3916 Prob gt chi2= 0000) and the Wald test con1047297rms that the independent variables are valid predictors (Wald chi2(45) = 59414 Prob gt chi2= 0000) A
speci1047297cation test performed on the 1047297xed effect model using a Pregibonrsquos goodness-of-link test shows good results (t = 077 P gt |t| = 0439)
c The dummy variables sev_event3 cat_event2 predict2 and comm_recov3 were omitted from the 1047297xed effect component for estimation purpose
Table 7 (Continued)
164 C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
The second potential limitation in our methodology relates to
the way the level of resilience of the households was assessed
While psychometric measurements are reliable and their results
replicable and testable when correctly implemented (Vigderhous
1977) one could fear that their use in the speci1047297c case of resilience
measurement could be subject to the effect of adaptive preference
that is the deliberate or re1047298exive process by which people adjust
their expectations and aspirations when trying to cope with
deterioration in living conditions (see eg Nussbaum 2001 Teschl
and Comim 2005) In our case this means that households
undergoing a degree of adaptive preference could have over-
estimated their ability to recover Although this risk is present we
tried to mitigate (or to reduce) it by introducing a qualifying
element in each of the coded answers of the resilience question-
naire so that respondents would have to associate the
1047297rst part of
their answer ldquoI have fully recoveredrdquo with a particular lsquoframe of
reference or quali1047297er (eg ldquoand it was not too dif 1047297cultrdquo) This frame
determined how they comprehend the questions being asked and
reduced the risk of the respondent simply relying on emotional
elements to answer these questions
Keeping in mind these potential limitations we now turn to
what we consider the most notable results of this research First is
the
lsquocumulative and continuous effect of shocks and stressors
whereby the impacts and disturbance of sequential shocksstressors and trends during the last 1047297ve years combine and
coalesce to create a constant non-stop stress We saw that the
nature and the source of events that were identi1047297ed by the
respondents in the four countries are all highly varied and
composite and reveal no speci1047297c clear pattern The events are a
combination of idiosyncratic and covariant sudden shocks and
long-term continuous trends Some are predictable while others
are totally unexpected All affect households simultaneously and
on an almost continuous basis The data suggests in particular that
on average households are hit by a new event every 16 months
This result calls into questions the framework generally used to
conduct shock or vulnerability assessment Often the approach has
been to disaggregate the problems people face and focus on single
threats such as eg 1047298ood or increase in food prices in order todevelop a clearer understanding of the impact of these particular
shocks and the ways people respond to them This approach has
been challenged however by a growing number of scholars who
argue that the reality households face on a daily basis is not linear
and mono-dimensional (OrsquoBrien and Leichenko 2000 Eriksen and
Silva 2009 Quinn et al 2011 McGregor 2011) Instead they argue
risks and vulnerability are often the product of multiple stressors
(Turner et al 2003 OrsquoBrien et al 2009) where social economic
political and biophysical factors interact combine and reinforce
each other to create a complex and dynamic multi-stressor multi-
shock environment (Reid and Vogel 2006 Adger 2006) Our
results corroborate this new interpretation
In line with this our analysis also shows that most households
engage in a suite of responses to a given shock On average
households adopted more than 4 types of responses to a particular
event This last result does not simply imply a rethinking of the way
shock or vulnerability assessments are conceptualized and
conducted see eg Turner et al (2003) or Leichenko and OrsquoBrien
(2008) It also demonstrates that the mental model (shock
gt response gt recovery) which is widely accepted in the
resilience literature is too simplistic and possibly misleading in
the sense that a state of (full) recovery may not exist This is at least
what was observed for the households included in our research
these households did not seem to have the chance or the time to
fully recover from one particular event before being affected by the
next Instead they were caught in what we could characterize as ldquoaconstant state of incomplete recoveringrdquo from new shocks and
stressors as illustrated in Fig 7
The next entry point in this discussion is wealth Our mixed
effect model (Table 7) shows that wealth was positively correlated
with household resilience Wealth has been identi1047297ed in the
literature as a key factor in strengthening the resilience of
households (Prowse and Scott 2008 WFP 2013) Analysis of
rural Ethiopian households hit by drought for instance showed that
while better-off households could sell livestock to smooth
consumption the poorer often tried to hold on to their livestock
at the expense of food consumption to preserve their options for
rebuilding herds The same study also shows that in the aftermath
of the hurricane Mitch in Honduras the relatively wealthy
households were able to rebuild their lost assets faster than thepoorest households for whom the effects of the hurricane were of
longer duration and felt much more acutely (Carter et al 2007) In
Fig 7 Left Current conceptualisation of resilience shock gt response gt recovery as presented in the literature [here redrawn from Carter et al 2007] Right actual
situation where the multi-stressor multi-shock environment induces that households are in a trajectory of continual and incomplete recovery Not represented here are the
multi-response
strategies
put
in
place
by
households
to
respond
to
these
adverse
events
C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170 165
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
disaster resilience National Disaster Resilience Roundtable Report 20September 2012 Melbourne Australia 36 p
Adger NW Dessai S Goulden M Hulme M Lorenzoni I Nelson DR Naess LO Wolf J Wreford A 2009 Are there social limits to adaptation to climatechange
Clim
Change
93
335ndash354Adger WN 2003 Social capital collective action and adaptation to climate
change Econ Geogr 79 (4) 387ndash404Adger WN 2006 Vulnerability Glob Environ Change 16 268ndash281Aldrich D 2010 Fixing recovery social capital in post-Crisis resilience J Homeland
Secur 6 1ndash10Ayers
J
Forsyth
T
2009
Community-based
adaptation
to
climate
changestrengthening resilience through development Environment 51 23ndash31
Beacuteneacute C Tew1047297k A 2001 Fishing effort allocation and 1047297shermenrsquos decision-makingprocess in a multi-species small-scale 1047297shery analysis of the conch and lobster1047297shery in Turks and Caicos Islands Hum Ecol 29 (2) 157ndash186
Beacuteneacute
C
Evans
L
Mills
D
Ovie
S
Raji
A
Ta1047297da
A
Kodio
A
Sinaba
F
Morand
PLemoalle J Andrew N 2011 Testing resilience thinking in a poverty contextexperience from the Niger river basin Glob Environ Change 21 (4) 1173ndash1184
Beacuteneacute C Godfrey-Wood R Newsham A Davies M2012 Resilience new utopia ornew tyranny
ndash Re1047298ection about the potentials and limits of the concept of
resilience
in
relation
to
vulnerability
reduction
programmes
IDS
Working
Paperno 405 Institute of Development Studies Brighton 61 p
Beacuteneacute C Newsham A Davies M Ulrichs M Godfrey-Wood R 2014 Resiliencepoverty and development J Int Dev 26 598ndash623
Beacuteneacute C Waid J Jackson-deGraffenried M Begum A Chowdhury M Skarin VRahman A Islam N Mamnun N Mainuddin K Shah MA 2015a Impact of climate-related
shocks
and
stresses
on
nutrition
and
food
security
in
ruralBangladesh Dhaka World Food Programme 119 p
Beacuteneacute C Frankenberger T Nelson S 2015b Design monitoring and evaluation of resilience interventions conceptual and empirical considerations IDS WorkingPaper no459 Institute of Development Studies 23 p
Beacuteneacute
C
2013
Towards
a
quanti1047297able
measure
of
resilience
IDS
Working
Paper
434Institute of Development Studies Brighton 27 p
Bandura A 1977 Self-ef 1047297cacy toward a unifying theory of behavioral changePsychol Rev 84 191ndash215
Baulch R Hoddinott J 2000 Economic mobility and poverty dynamics indeveloping countries J Dev Stud 36 (6) 1ndash23
Belhabib
D
Sumaila
UR
Pauly
D
2015
Feeding
the
poor
contribution
of
WestAfrican 1047297sheries to employment and food security Ocean Coast Manage 11172ndash81
Berkes F Folke C 1998 Linking social and ecological systems for resilience andsustainability In Berkes F Folke C (Eds) Linking Social and EcologicalSystems Management Practices and Social Mechanisms for Building ResilienceCambridge University Press Cambridge pp 1ndash25
Bernier Q Meinzen-Dick R 2014 Resilience and social capital Building Resiliencefor Food and Nutrition Security Conference Paper No 4 International FoodPolicy Research Institute Washington DC 26 p
Bhattamishra R Barrett C 2010 Community-Based risk managementarrangements a review World Dev 38 (7) 923ndash932
Boarini R Kolev A McGregor JA 2014 Measuring well-being and progress incountries at different stages of development towards a more universalconceptual framework OECD Working Paper No 235 Organisation forEconomic Co-operation and Development Development Center
ndash Better Life
Initiative Paris 59 p
Boyd E Osbahr H Ericksen P Tompkins E Carmen Lemos M Miller F 2008Resilience and
lsquoclimatizingrsquo development examples and policy implicationsDevelopment 51 390ndash396
Cam1047297eld
L
McGregor
JA
2005
Resilience
and
wellbeing
in
developing
countriesIn Ungar M (Ed) Handbook for Working with Children and Youth Pathwaysto Resilience Across Cultures and Contexts Sage Publications Thousand OaksCA
Cam1047297eld
L
Ruta
D
2007
Translation
is
not
enough
using
the
Global
PersonGenerated Index (GPGI) to assess individual quality of life in BangladeshThailand and Ethiopia Qual Life 16 (6) 1039ndash1051
Carter M Little P Mogues T Negatu W 2007 Poverty traps and natural disastersin Ethiopia and Honduras World Dev 35 (5) 835ndash856
Cleaver
F
2005
The
inequality
of
social
capital
and
the
reproduction
of
chronicpoverty World Dev 33 (6) 893ndash906
Constas M Frankenberger T Hoddinott J 2014a Resilience measurementprinciples toward an agenda for measurement design Resilience MeasurementTechnical Working Group Technical Series No 1 Food Security informationNetwork Rome
Constas MT Frankenberger J Hoddinott N Mock D Romano C Beacuteneacute DMaxwell 2014b A common analytical model for resilience measurementcausal framework and methodological options Food Security InformationNetwork (FSIN) Technical Series No 2 World Food Programme Rome
Coulthard S 2011 More than just access to 1047297sh the pros and cons of 1047297sherparticipation
in
a
customary
marine
tenure
(Padu)
system
under
pressure
MarPolicy 35 405ndash412
DFID 2011 De1047297ning Disaster Resilience A DFID Approach Paper Department forInternational Development London pp 20
Dercon S Hoddinott J Woldehanna T 2005 Shocks and consumption in 15ethiopian
villages
1999ndash2004
J
Afr
Econ
14
(4)
559ndash585Dercon S 1996 Risk crop choice and savings evidence from Tanzania Econ Dev
Cult Change 44 (3) 485ndash513Duit A Galaz V Eckerberg K 2010 Governance complexity and resilience Glob
Environ Change 20 (3) 363ndash368Eriksen
SEH
Silva
JA
2009
The
vulnerability
context
of
a
savannah
area
inMozambique household drought coping strategies and responses to economicchange Environ Sci Policy 12 (1) 33ndash52
Fafchamps M Lund S 2003 Risk-Sharing networks in rural Philippines J DevEcon 71 (2) 261ndash287
Frankenberger T Nelson S 2013 Background Paper for the Expert Consultation onResilience
Measurement
for
Food
Security
TANGO
International
Rome
Foodand Agricultural Organization and World Food Program
Heltberg R Siegel PS Jorgensen SL 2009 Addressing human vulnerability toclimate change towards a
lsquono-regretsrsquo approach Glob Environ Change 19 89ndash99
Hoddinott
J
Dercon
S
Krishnan
P
2009
Networks
and
informal
mutual
supportin 15 ethiopian villages a description In Kirsten JF Dorward AR Poulton CVink N (Eds) Institutional Economics Perspectives on African AgriculturalDevelopment International Food Policy Research Institute Washington DC pp273ndash286
Hoddinott
J
2006
Shocks
and
their
consequences
across
and
within
households
inRural Zimbabwe J Dev Stud 42 (2) 301ndash321
Intergovernmental Panel on Climate Change (IPCC) 2012 In Field CB Barros VStocker TF Qin D Dokken DJ Ebi KL Mastrandrea MD Mach KJPlattner G-K Allen SK Tignor MMidgley PM (Eds) Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation A SpecialReport of Working Groups I and II of the Intergovernmental Panel on ClimateChange Cambridge University Press Cambridge UK
Jackson T 2005 Motivating sustainable consumptionmdasha review of evidence onconsumer behaviour and behavioural change A Report to the Sustainable
Event type (Vietnam) Reduce
expenditures
Borrow
money
Reduce
Food
Change
1047297shing
strategy
Get
support
Increase
1047297shing
effort
Diversi1047297cation Seek new
collaboration
Migration Exit the
1047297shery
Sell
assets
Total
Others (aggregated) 4 7 4 6 3 0 1 3 0 0 2 30
Erosion 2 4 2 1 6 2 2 2 3 1 25
Catch reduced
suddenly
8 4 6 7 1 2 4 2 34
Gears lost 10 18 6 5 1 2 1 43
Cold wind prolongs 15 7 11 3 1 7 2 46
Typhoon
12
11
10
2
4
2
3
5
4
1
1
55
Illness
11 14
6
2
11
2
2
4
1
1
2
56Food price increase 20 17 19 2 8 5 1 72
Input price increase
continuously
47 39 33 21 40 5 6 16 1 208
Big boats compete
ground and catch
54 39 32 40 9 19 11 15 8 3 2 232
Catch
reduced
continuously
102
70
80
63
22
51
51
25
23
17
6
510
Total 285 230 209 152 105 91 87 75 39 23 15 1311
C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170 169
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
Development Research Network Centre for Environmental StrategiesUniversity of Surrey
Jones L Boyd E 2011 Exploring social barriers to adaptation insights fromWestern Nepal Glob Environ Change 21 (4) 1262ndash1274
Kallstrom HN Ljung M 2005 Social sustainability and collaborative learningAmbio 34 376ndash382
Kelty R Kelty R 2011 Human dimensions of a 1047297shery at a crossroads resourcevaluation identity and way of life in a seasonal 1047297shing community Soc NatResour
24
(4)
334ndash348Klein RJT Nicholls RJ Thomalla F 2003 Resilience to natural hazards how
useful is this concept Environ Hazards 5 35ndash45
Krosnick
JA
Fabrigar
LR
1997
Designing
rating
scales
for
effective
measurementin surveys In Lyberg L Biemer P Collins M de Leeuw E Dippo C SchwarzN
Trewin
D
(Eds)
Survey
Measurement
and
Process
Quality
John
Wiley
andSons Inc New York NY pp 141ndash164
Leichenko R OrsquoBrien K 2008 Environmental Change and Globalization DoubleExposures Oxford University Press New York
Marschke M Berkes F 2006 Exploring Strategies that build livelihood resiliencea case from Cambodia Ecol Soc 11 (1) httpwwwecologyandsocietyorgvol11iss1art42
McGregor JA Cam1047297eld L Woodcock A 2009 Needs wants and goals wellbeingquality
of
life
and
public
policy
Appl
Res
Qual
Life
4
135ndash154McGregor JA 1994 Village credit and the reproduction of poverty in rural
Bangladesh In Acheson J (Ed) Economic Anthropology and the NewInstitutional Economics University Press of AmericaSociety for EconomicAnthropology Washington pp 261ndash281 (Chapter)
McGregor
JA
2011
Reimagining
development
through
the
crisis
watch
initiative
IDS Bull 42 (5) 17ndash23McLaughlin P Dietz T 2007 Structureagency and environment toward an
integrated perspective on vulnerability Glob Environ Change 39 (4) 99ndash111Meyer MA 2013 Social capital and resilience in the context of disaster social
capital
and
collective
ef 1047297cacy
for
disaster
resilience
connecting
individualswith communities and vulnerability with resilience in hurricane-pronecommunities in Florida PhD Dissertation Department of sociology Coloradostate University Fort Collins Colorado (311 p)
Mills DJ Adhuri D Phillips M Ravikumar B Padiyar AP 2011 Shocks recoverytrajectories and resilience among aquaculture-dependent households in post-tsunami
Aceh
Indonesia
Local
Environ
Int
J
Justice
Sustain
16
(5)
425ndash444Morduch J 1995 Income smoothing and consumption smoothing J Econ
Perspect 9 (3) 103ndash114Morris S Carletto C Hoddinott J Christiaensen L 2000 J Epidemiol Commun
Health 54 381ndash387Myers
RA
Worm
B
2003
Rapid
worldwide
depletion
of
predatory 1047297sh
communities Nature 423 280ndash283Nakagawa Y Shaw R 2004 Social capital a missing link to disaster recovery Int J
Mass
Emerg
Disasters
22
(1)
5ndash
34Nussbaum MC 2001 Adaptive preferences and womenrsquos options Econ Philos 1767ndash88
Oslashstergaard N Reenberg A 2010 Cultural barriers to climate change adaptation acase study from Northern Burkina Faso Glob Environ Change 20 (1) 142ndash152
OrsquoBrien K Leichenko R 2000 Double exposure assessing the impacts of climatechange within the context of economic globalization Glob Environ Change 10221ndash232
OrsquoBrien K Eriksen S Sygna L Naess LO 2006 Questioning complacencyclimate change impacts vulnerability and adaptation in Norway AMBIO JHum Environ 35 (2) 50ndash56
OrsquoBrien K Quilan T Ziervogel G 2009 Vulnerability interventions in the contextof multiple stressors lessons from the Southern Africa vulnerability initiative(SAVI) Environ Sci Policy 12 23ndash32
OrsquoRiordan T Jordan A 1999 Institutions climate change and cultural theorytowards a common analytical framework Glob Environ Change 9 (2) 81ndash93
Pain A Levine S 2012 A conceptual analysis of livelihoods and resilienceaddressing the
lsquoinsecurity of agency HPG Working Paper OverseasDevelopment Institute Humanitarian Policy Group London
Pauly D Christensen V Dalsgaard Froese JR Torres F 1998 Fishing downmarine food webs Science 279 (5352) 860ndash863
Pelling M Manuel-Navarrete D 2011 From resilience to transformation theadaptive cycle in two Mexican urban centersEcol Soc 16 (2)11 (online) httpwwwecologyandsocietyorgvol16iss2art11
Prowse
M
Scott
L
2008
Assets
and
adaptation
an
emerging
debate
IDS
Bull
39(4) 42ndash52
Putzel J 1997 Accounting for the lsquodark sidersquo of social capital reading Robert
Putnam
on
democracy
J
Int
Dev
9
(7)
939ndash949
Quinn CH Ziervogel G Taylor A Takama T Thomalla F 2011 Coping withmultiple
stresses
in
rural
South
Africa
Ecol
Soc
16
(3)
doihttpdxdoiorg105751ES-04216-160302
Reid P Vogel C 2006 Living and responding to multiple stressors in South Africamdashglimpses from KwaZulu-Natal Glob Environ Change 16 (2) 195ndash206
Roncoli C Ingram K Kirshen P 2001 The costs and risks of coping with droughtlivelihood
impacts
and
farmersrsquo
responses
in
Burkina
Faso
Clim
Res
19
119ndash132
Schwarz AM Beacuteneacute C Bennett G Boso D Hilly Z Paul C Posala R Sibiti SAndrew N 2011 Vulnerability and resilience of rural remote communities toshocks and global changes empirical analysis from the Solomon Islands GlobEnviron Change 21 1128ndash1140
Sinha
S
Lipton
M
Yaqub
S
2002
Poverty
and
damaging 1047298uctuations
how
dothey relate J Asian Afr Stud 37 (2) 186ndash243
Tansey J OrsquoRiordan T 1999 Cultural theory and risk a review Health Risk Soc 171ndash90
Teschl M Comim F 2005 Adaptive preferences and capabilities somepreliminary
conceptual
explorations
Rev
Soc
Econ
63
(2)
229ndash247
Trimble M Johnson D 2013 Artisanal 1047297shing as an undesirable way of life Theimplications for governance of 1047297shersrsquo wellbeing aspirations in coastal Uruguayand southeastern Brazil Mar Policy 37 37ndash44
Turner BL Kasperson RE Matson P McCarthy JJ Corell RW Christensen LEckley
N
Kasperson
JX
Luers
A
Martello
ML
Polsky
C
Pulsipher
ASchiller A 2003 A framework for vulnerability analysis in sustainabilityscience Proc Natl Acad Sci 100 (14) 8074ndash8079
Vigderhous G 1977 The level of measurement and
lsquoPermissiblersquo statistical analysisin social research Pac Sociol Rev 20 (1) 61ndash72
WFP 2013 Building Resilience Through Asset Creation Resilience and PreventionUnit
Policy
Programme
and
Innovation
Division
World
Food
Program
Rome(23 p)
Walker B Carpenter S Anderies J Abel N Cumming GS Janssen M Lebel LN J Peterson GD Pritchard R 2002 Resilience management in social-ecological systems a working hypothesis for a participatory approach ConservEcol
6
(1)
14Weber EU 2010 What shapes perceptions of climate change Clim Change 1 (3)
332ndash342
Wolf
J
Adger
WN
Lorenzoni
I
Abrahamson
V
Raine
R
2010
Social
capitalindividual responses to heat waves and climate change adaptation an empiricalstudy
of
two
UK
cities
Glob
Environ
Change
20
44ndash52Wood G 2003 Staying secure staying poor the Faustian bargain World Dev 31
(3) 455ndash471World Bank 2011 Building Resilience and Opportunities World Bankrsquos Social
Protection and Labour Strategy 2012ndash2022 World Bank Washington DCYamano T Alderman H Christiaensen L 2003 Child Growth Shocks and Food
Aid in Rural Ethiopia World Bank Washington DCZimmerman F Carter M 2003 Asset smoothing consumption smoothing and the
reproduction of inequality under risk and subsistence constraints J Dev Econ71 233ndash260
von Grebmer K Headey D Beacuteneacute C Haddad L et al 2013 Global Hunger IndexThe Challenge of Hunger Building Resilience to Achieve Food and NutritionSecurity Welthungerhilfe International Food Policy Research Institute andConcern Worldwide Bonn Washington DC and Dublin
170 C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
The type of responses adopted by households was included in
the model to test whether the level of resilience of households is
effectively in1047298uenced by those responses Amongst the 11 types of
responses tested three have statistically signi1047297cant signs engag-
ing
in
new
collaboration
(negative
sign
P
=
0001)
increasing1047297shing effort (positive P lt 00001) and quitting the
1047297shery
(negative P = 0047) The negative correlation found between
household resilience and the strategy that consists of forming new
collaboration may be dif 1047297cult to interpret as it can re1047298ect many
highly contextual factors The two others responses and the signs
of their correlations (one negative sign for leaving the sector and
one positive sign for increasing 1047297shing effort) are initially
disturbing but eventually not too surprising Disturbing
1047297rst
because this
1047297nding does not lead to the type of long-term
behaviours that appeal to policy makers and 1047297shery managers On
the contrary they would rather see 1047297shing effort reductions and
exit strategies more often adopted by
1047297shers in particular in the
context of the current world
1047297shery crisis Not surprising however
because this result is in line with what one could expect from
1047297sherfolks after an adverse event in the face of a long-term stress
(such
as
the
drop
in
income
following
a
continuous
decline
in
1047297shcatch) or a sudden need for cashrevenues (as a consequence of
eg destruction of 1047297shing gear induced by bad weather or the
need to pay health bills)
1047297shers are often observed to alter their
1047297shing activities to make up for these events usually by changing
adjusting their 1047297shing strategy (eg switching between targeted
species andor
1047297shing gear) or increasing their
1047297shing effort (eg
investing in more ef 1047297cient
1047297shing gear increasing the quantity of
gear used or increasing the number of days at sea) in an attempt to
generate more cash In that context it is not surprising that the
majority of 1047297shing households interviewed in this research
consider that their ability to
lsquobounce back following an adverse
event was enhanced when they increase their 1047297shing effort
Additionally given what we know about their strong sense of
identity
(Kelty
and
Kelty
2011
Trimble
and
Johnson
2013) but
alsothe importance of peer-pressure and reputation (see eg Beacuteneacute and
Tew1047297k 2001) quitting the 1047297shery would certainly be perceived by
many 1047297shers as a failure thus the negative correlation between
(perceived) resilience and leaving the sector
The next category of variables which was investigated through
the model was the Quality of Life indicators (see Table 3 for a
recall) A reasonable hypothesis although not explicitly formu-
lated in the
lsquoworking hypotheses section above- is that some of
these QoL indices may have a positive effect on the ability of
households to handle and recover from adverse events One can
indeed assume that households satis1047297ed in many of the
dimensions of wellbeing which they considers important (such
as say access to health services or to public infrastructure) may
feel better equipped to reactrespond to any particular event than
Table 5
Top comparison of propensities to adopt particular types of responses for households characterized by high (N = 224) and low (N = 235) subjective resilience Bottom
comparison of the two same groups in terms of asset levels education and age of the household head
Responses subjective
resilience
level
Mean [95 Conf
Interval]
test resulta
Coping strategies High 198 1840 2136 t = 43037 Pr(|T| gt |
t|) = 0000
Low 245 2311 2596
Social-relation-based strategies High 083 0738 0927 t = 05187 Pr(|T| gt |
t|) = 0604
Low 086 0787 0943
Fishing-related strategies High 083 0732 0935 t = 03267 Pr(|T| gt |
t|)
=
0744
Low 081 0715 0906
Non-1047297shery
strategies
High
067
0559
0794
t
=
35599
Pr(|T|
gt
|
t|) = 0000
Low 042 0341 0502
Household characteristics
Asset High 768 7218 8157 t = 08882 Pr(|T| gt |
t|) = 0374
Low 739 6938 7848
Education High 796 7338 8599 t = 10186 Pr(|T| gt |
t|)
=
0308
Low 750 6857 8147
Age High 4688 45377 48391 t = 01332 Pr(|T| gt |
t|) = 0894
Low 4702 45570 48482
p
lt 5
p
lt 1
p
lt 1
a mean difference unpaired t -test Ho Diff = 0 Ha diff 6frac14 0
C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170 161
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
diversif non 1047297sher diversi1047297cation dummy 1 = yes
exit_1047297sh exit the 1047297shery sector dummy 1 = yes
migrat migrate dummy 1 = yes
quality of life indices
index_incom
income
index
ordinal
variable
coded
[-6
+6]
ndash6
=
very
poor
+6
=
very
strong
index_livelih livelihood index ordinal variable coded [-6 +6] ndash6 = very poor +6 = very strongindex_housing housing and infrastructure index ordinal variable coded [-6 +6] ndash6 = very poor +6 = very strong
index_educ education index ordinal variable coded [-6 +6]
ndash6 = very poor +6 = very strong
index_soc social capital index ordinal variable coded [-6 +6]
ndash6 = very poor +6 = very strong
index_health health index ordinal variable coded [-6 +6] ndash6 = very poor +6 = very strong
ind_emp empowerment index ordinal variable coded [-6 +6]
ndash6 = very poor +6 = very strong
index_soc_cris social capital index in time of crisis
ndash6 = very poor +6 = very strong
index_emp_cris empowerment index in time of crisis
ndash6 = very poor +6 = very strong
index_spirit index of spirituality
ordinal variable coded [-6 +6]
ndash6 = very poor +6 = very strong
household characteristics
HH head sex sex of household head dummy 1 = female
HH
head
age
age
of
household
head
age
in
years
HH head educ level of education of the household head 0 = no education 20 = post-graduate level
HH size size of household number of members (not adjusted for age)
log_asset household assets (log-transformed) value of household assets (proxy for wealth level)
community
resiliencecomm_recov level of recovery of the community
a Fitting a three level model requires two random-effect equations one for level three (country) and one for level two (community) with i = 1 nvc 1047297rst level of
observation (households) nested within k = 1 8 s level cluster (community) nested within j = 1 4 third level cluster (country)
162 C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
community level in the same way than the QoL indices that is by
averaging the scores obtained at the individual household level)
The best correlation was obtained with the QoL index of social
capital in time of crisis (R 2= 077 F = 0004) see Fig 6- suggesting
that communities with higher social capital in time of crisis are
also characterized by higher level of resilience
5 Discussion
Resilience has been increasingly recognized as a potentially
useful concept to help practitioners academics and policy-makers
better understand the links between shocks response and longer-
term development outcomes (Constas et al 2014a Beacuteneacute et al
2014) Incorporating resilience alongside vulnerability analysis can
contribute an essential element to societal ability to better prepare
for future shocks and stressors This paper argues that improving
our understanding of what contributes to or constitutes peoplersquos
resilience requires not only the development and
1047297eld-testing of
robust and measurable indices (Beacuteneacute 2013 Constas et al 2014b)
but also a better insight into the social factors including
knowledge perceptions and motivations- that in1047298uence and affect
individual and collective capacity to respond to shocks and
stressors
Our analysis conducted in eight 1047297shery-dependent communi-
ties from Fiji Ghana Sri Lanka and Vietnam reveals a series of
notable results in relation to these questions In considering these
outcomes it is important to 1047297rst take stock of potential limitations
pitfalls or biases in the study methodology Given the nature of the
1047297ndings two potential issues require further consideration First is
the question of how representative our sampling methodology
was It could be argued for instance that the observed low adoption
rates of non-1047297shery strategiesndash and in particular the low score of
the
lsquoexiting the
1047297sheryrsquo was driven by our sampling method
underrepresenting these groups as those who had effectively left
the 1047297shery were not included in the sample
The FGDs that preceded the household survey speci1047297cally
addressed this issue In Sri Lanka for instance the opening question
prompted participants (both men and women) to discuss whether
ldquo1047297shers in their community had ever left 1047297sheries due to their
inability to cope with adverse eventsrdquo The answer was that it
generally does not happen with the notable exception of someyoung
1047297shers who attempted to migrate to Australia through
illegal means If it occurred exiting the 1047297shery was said to be
temporary ldquothey may leave the village or 1047297shing but will come
back when the situation is favourablerdquo In Vietnam the sampling
was speci1047297cally designed to cover both
1047297shers and ex-1047297shers in
proportions represented in the community As a result 9 ex-1047297shers
were included in the sample Overall therefore although we were
unable to conceive of a completely representative sampling design
(in the statistical sense) the parallel information that was collected
in the FGDs and the individual households converge to suggest that
exiting the
1047297shery was not an option envisaged by the members of
these different communities and consequently that our sampling
was not too severely biased
0
2
4
6
8
10
12
14
16
-05 05 15 25
C o m m u n i t y l e v e l r e s i l i
e n c e i n d e x
Community level social capital in me of crisis
Fiji
Ghana
Sri Lanka
Vietnam
Fig 6 Correlation between social capital in time of crisis and resilience index
across the eight communities The straight line represents the linear relation
(R 2 = 077 F = 0004) and the bars are 95 con1047297dence intervals for each community
Random-effects parameters St Dev Std Err [95 Conf Interval]
country level
index_incom 043 024 0146 1266
index_livelih 051 027 0175 1464
index_housing 013 013 0018 0962
index_soc 039 024 0119 1303
index_soc_cris
078
038
0300
2009index_educ 015 013 0028 0834
const 090 067 0209 3861
community level
const 032 026 0066 1534
residuals 277 008 2617 2923
LR test vs linear regression chi2(7) = 3916 Prob gt chi2= 0000
p
lt 5
p
lt
1 p lt 1ma Fitting a three level model requires two random-effect equations one for level three (country) and one for level two (community) with i = 1 nvc 1047297rst level of
observation
(households)
nested
within
k
=
1
8
second
level
cluster
(community)
nested
within
j
=
1
4
third
level
cluster
(country)b The likelihood-ratio (LR) test comparing the nested mixed-effects model with the corresponding 1047297xed effect model con1047297rms the appropriate use of the mixed effect
model (chi2(7) = 3916 Prob gt chi2= 0000) and the Wald test con1047297rms that the independent variables are valid predictors (Wald chi2(45) = 59414 Prob gt chi2= 0000) A
speci1047297cation test performed on the 1047297xed effect model using a Pregibonrsquos goodness-of-link test shows good results (t = 077 P gt |t| = 0439)
c The dummy variables sev_event3 cat_event2 predict2 and comm_recov3 were omitted from the 1047297xed effect component for estimation purpose
Table 7 (Continued)
164 C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
The second potential limitation in our methodology relates to
the way the level of resilience of the households was assessed
While psychometric measurements are reliable and their results
replicable and testable when correctly implemented (Vigderhous
1977) one could fear that their use in the speci1047297c case of resilience
measurement could be subject to the effect of adaptive preference
that is the deliberate or re1047298exive process by which people adjust
their expectations and aspirations when trying to cope with
deterioration in living conditions (see eg Nussbaum 2001 Teschl
and Comim 2005) In our case this means that households
undergoing a degree of adaptive preference could have over-
estimated their ability to recover Although this risk is present we
tried to mitigate (or to reduce) it by introducing a qualifying
element in each of the coded answers of the resilience question-
naire so that respondents would have to associate the
1047297rst part of
their answer ldquoI have fully recoveredrdquo with a particular lsquoframe of
reference or quali1047297er (eg ldquoand it was not too dif 1047297cultrdquo) This frame
determined how they comprehend the questions being asked and
reduced the risk of the respondent simply relying on emotional
elements to answer these questions
Keeping in mind these potential limitations we now turn to
what we consider the most notable results of this research First is
the
lsquocumulative and continuous effect of shocks and stressors
whereby the impacts and disturbance of sequential shocksstressors and trends during the last 1047297ve years combine and
coalesce to create a constant non-stop stress We saw that the
nature and the source of events that were identi1047297ed by the
respondents in the four countries are all highly varied and
composite and reveal no speci1047297c clear pattern The events are a
combination of idiosyncratic and covariant sudden shocks and
long-term continuous trends Some are predictable while others
are totally unexpected All affect households simultaneously and
on an almost continuous basis The data suggests in particular that
on average households are hit by a new event every 16 months
This result calls into questions the framework generally used to
conduct shock or vulnerability assessment Often the approach has
been to disaggregate the problems people face and focus on single
threats such as eg 1047298ood or increase in food prices in order todevelop a clearer understanding of the impact of these particular
shocks and the ways people respond to them This approach has
been challenged however by a growing number of scholars who
argue that the reality households face on a daily basis is not linear
and mono-dimensional (OrsquoBrien and Leichenko 2000 Eriksen and
Silva 2009 Quinn et al 2011 McGregor 2011) Instead they argue
risks and vulnerability are often the product of multiple stressors
(Turner et al 2003 OrsquoBrien et al 2009) where social economic
political and biophysical factors interact combine and reinforce
each other to create a complex and dynamic multi-stressor multi-
shock environment (Reid and Vogel 2006 Adger 2006) Our
results corroborate this new interpretation
In line with this our analysis also shows that most households
engage in a suite of responses to a given shock On average
households adopted more than 4 types of responses to a particular
event This last result does not simply imply a rethinking of the way
shock or vulnerability assessments are conceptualized and
conducted see eg Turner et al (2003) or Leichenko and OrsquoBrien
(2008) It also demonstrates that the mental model (shock
gt response gt recovery) which is widely accepted in the
resilience literature is too simplistic and possibly misleading in
the sense that a state of (full) recovery may not exist This is at least
what was observed for the households included in our research
these households did not seem to have the chance or the time to
fully recover from one particular event before being affected by the
next Instead they were caught in what we could characterize as ldquoaconstant state of incomplete recoveringrdquo from new shocks and
stressors as illustrated in Fig 7
The next entry point in this discussion is wealth Our mixed
effect model (Table 7) shows that wealth was positively correlated
with household resilience Wealth has been identi1047297ed in the
literature as a key factor in strengthening the resilience of
households (Prowse and Scott 2008 WFP 2013) Analysis of
rural Ethiopian households hit by drought for instance showed that
while better-off households could sell livestock to smooth
consumption the poorer often tried to hold on to their livestock
at the expense of food consumption to preserve their options for
rebuilding herds The same study also shows that in the aftermath
of the hurricane Mitch in Honduras the relatively wealthy
households were able to rebuild their lost assets faster than thepoorest households for whom the effects of the hurricane were of
longer duration and felt much more acutely (Carter et al 2007) In
Fig 7 Left Current conceptualisation of resilience shock gt response gt recovery as presented in the literature [here redrawn from Carter et al 2007] Right actual
situation where the multi-stressor multi-shock environment induces that households are in a trajectory of continual and incomplete recovery Not represented here are the
multi-response
strategies
put
in
place
by
households
to
respond
to
these
adverse
events
C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170 165
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
disaster resilience National Disaster Resilience Roundtable Report 20September 2012 Melbourne Australia 36 p
Adger NW Dessai S Goulden M Hulme M Lorenzoni I Nelson DR Naess LO Wolf J Wreford A 2009 Are there social limits to adaptation to climatechange
Clim
Change
93
335ndash354Adger WN 2003 Social capital collective action and adaptation to climate
change Econ Geogr 79 (4) 387ndash404Adger WN 2006 Vulnerability Glob Environ Change 16 268ndash281Aldrich D 2010 Fixing recovery social capital in post-Crisis resilience J Homeland
Secur 6 1ndash10Ayers
J
Forsyth
T
2009
Community-based
adaptation
to
climate
changestrengthening resilience through development Environment 51 23ndash31
Beacuteneacute C Tew1047297k A 2001 Fishing effort allocation and 1047297shermenrsquos decision-makingprocess in a multi-species small-scale 1047297shery analysis of the conch and lobster1047297shery in Turks and Caicos Islands Hum Ecol 29 (2) 157ndash186
Beacuteneacute
C
Evans
L
Mills
D
Ovie
S
Raji
A
Ta1047297da
A
Kodio
A
Sinaba
F
Morand
PLemoalle J Andrew N 2011 Testing resilience thinking in a poverty contextexperience from the Niger river basin Glob Environ Change 21 (4) 1173ndash1184
Beacuteneacute C Godfrey-Wood R Newsham A Davies M2012 Resilience new utopia ornew tyranny
ndash Re1047298ection about the potentials and limits of the concept of
resilience
in
relation
to
vulnerability
reduction
programmes
IDS
Working
Paperno 405 Institute of Development Studies Brighton 61 p
Beacuteneacute C Newsham A Davies M Ulrichs M Godfrey-Wood R 2014 Resiliencepoverty and development J Int Dev 26 598ndash623
Beacuteneacute C Waid J Jackson-deGraffenried M Begum A Chowdhury M Skarin VRahman A Islam N Mamnun N Mainuddin K Shah MA 2015a Impact of climate-related
shocks
and
stresses
on
nutrition
and
food
security
in
ruralBangladesh Dhaka World Food Programme 119 p
Beacuteneacute C Frankenberger T Nelson S 2015b Design monitoring and evaluation of resilience interventions conceptual and empirical considerations IDS WorkingPaper no459 Institute of Development Studies 23 p
Beacuteneacute
C
2013
Towards
a
quanti1047297able
measure
of
resilience
IDS
Working
Paper
434Institute of Development Studies Brighton 27 p
Bandura A 1977 Self-ef 1047297cacy toward a unifying theory of behavioral changePsychol Rev 84 191ndash215
Baulch R Hoddinott J 2000 Economic mobility and poverty dynamics indeveloping countries J Dev Stud 36 (6) 1ndash23
Belhabib
D
Sumaila
UR
Pauly
D
2015
Feeding
the
poor
contribution
of
WestAfrican 1047297sheries to employment and food security Ocean Coast Manage 11172ndash81
Berkes F Folke C 1998 Linking social and ecological systems for resilience andsustainability In Berkes F Folke C (Eds) Linking Social and EcologicalSystems Management Practices and Social Mechanisms for Building ResilienceCambridge University Press Cambridge pp 1ndash25
Bernier Q Meinzen-Dick R 2014 Resilience and social capital Building Resiliencefor Food and Nutrition Security Conference Paper No 4 International FoodPolicy Research Institute Washington DC 26 p
Bhattamishra R Barrett C 2010 Community-Based risk managementarrangements a review World Dev 38 (7) 923ndash932
Boarini R Kolev A McGregor JA 2014 Measuring well-being and progress incountries at different stages of development towards a more universalconceptual framework OECD Working Paper No 235 Organisation forEconomic Co-operation and Development Development Center
ndash Better Life
Initiative Paris 59 p
Boyd E Osbahr H Ericksen P Tompkins E Carmen Lemos M Miller F 2008Resilience and
lsquoclimatizingrsquo development examples and policy implicationsDevelopment 51 390ndash396
Cam1047297eld
L
McGregor
JA
2005
Resilience
and
wellbeing
in
developing
countriesIn Ungar M (Ed) Handbook for Working with Children and Youth Pathwaysto Resilience Across Cultures and Contexts Sage Publications Thousand OaksCA
Cam1047297eld
L
Ruta
D
2007
Translation
is
not
enough
using
the
Global
PersonGenerated Index (GPGI) to assess individual quality of life in BangladeshThailand and Ethiopia Qual Life 16 (6) 1039ndash1051
Carter M Little P Mogues T Negatu W 2007 Poverty traps and natural disastersin Ethiopia and Honduras World Dev 35 (5) 835ndash856
Cleaver
F
2005
The
inequality
of
social
capital
and
the
reproduction
of
chronicpoverty World Dev 33 (6) 893ndash906
Constas M Frankenberger T Hoddinott J 2014a Resilience measurementprinciples toward an agenda for measurement design Resilience MeasurementTechnical Working Group Technical Series No 1 Food Security informationNetwork Rome
Constas MT Frankenberger J Hoddinott N Mock D Romano C Beacuteneacute DMaxwell 2014b A common analytical model for resilience measurementcausal framework and methodological options Food Security InformationNetwork (FSIN) Technical Series No 2 World Food Programme Rome
Coulthard S 2011 More than just access to 1047297sh the pros and cons of 1047297sherparticipation
in
a
customary
marine
tenure
(Padu)
system
under
pressure
MarPolicy 35 405ndash412
DFID 2011 De1047297ning Disaster Resilience A DFID Approach Paper Department forInternational Development London pp 20
Dercon S Hoddinott J Woldehanna T 2005 Shocks and consumption in 15ethiopian
villages
1999ndash2004
J
Afr
Econ
14
(4)
559ndash585Dercon S 1996 Risk crop choice and savings evidence from Tanzania Econ Dev
Cult Change 44 (3) 485ndash513Duit A Galaz V Eckerberg K 2010 Governance complexity and resilience Glob
Environ Change 20 (3) 363ndash368Eriksen
SEH
Silva
JA
2009
The
vulnerability
context
of
a
savannah
area
inMozambique household drought coping strategies and responses to economicchange Environ Sci Policy 12 (1) 33ndash52
Fafchamps M Lund S 2003 Risk-Sharing networks in rural Philippines J DevEcon 71 (2) 261ndash287
Frankenberger T Nelson S 2013 Background Paper for the Expert Consultation onResilience
Measurement
for
Food
Security
TANGO
International
Rome
Foodand Agricultural Organization and World Food Program
Heltberg R Siegel PS Jorgensen SL 2009 Addressing human vulnerability toclimate change towards a
lsquono-regretsrsquo approach Glob Environ Change 19 89ndash99
Hoddinott
J
Dercon
S
Krishnan
P
2009
Networks
and
informal
mutual
supportin 15 ethiopian villages a description In Kirsten JF Dorward AR Poulton CVink N (Eds) Institutional Economics Perspectives on African AgriculturalDevelopment International Food Policy Research Institute Washington DC pp273ndash286
Hoddinott
J
2006
Shocks
and
their
consequences
across
and
within
households
inRural Zimbabwe J Dev Stud 42 (2) 301ndash321
Intergovernmental Panel on Climate Change (IPCC) 2012 In Field CB Barros VStocker TF Qin D Dokken DJ Ebi KL Mastrandrea MD Mach KJPlattner G-K Allen SK Tignor MMidgley PM (Eds) Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation A SpecialReport of Working Groups I and II of the Intergovernmental Panel on ClimateChange Cambridge University Press Cambridge UK
Jackson T 2005 Motivating sustainable consumptionmdasha review of evidence onconsumer behaviour and behavioural change A Report to the Sustainable
Event type (Vietnam) Reduce
expenditures
Borrow
money
Reduce
Food
Change
1047297shing
strategy
Get
support
Increase
1047297shing
effort
Diversi1047297cation Seek new
collaboration
Migration Exit the
1047297shery
Sell
assets
Total
Others (aggregated) 4 7 4 6 3 0 1 3 0 0 2 30
Erosion 2 4 2 1 6 2 2 2 3 1 25
Catch reduced
suddenly
8 4 6 7 1 2 4 2 34
Gears lost 10 18 6 5 1 2 1 43
Cold wind prolongs 15 7 11 3 1 7 2 46
Typhoon
12
11
10
2
4
2
3
5
4
1
1
55
Illness
11 14
6
2
11
2
2
4
1
1
2
56Food price increase 20 17 19 2 8 5 1 72
Input price increase
continuously
47 39 33 21 40 5 6 16 1 208
Big boats compete
ground and catch
54 39 32 40 9 19 11 15 8 3 2 232
Catch
reduced
continuously
102
70
80
63
22
51
51
25
23
17
6
510
Total 285 230 209 152 105 91 87 75 39 23 15 1311
C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170 169
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
Development Research Network Centre for Environmental StrategiesUniversity of Surrey
Jones L Boyd E 2011 Exploring social barriers to adaptation insights fromWestern Nepal Glob Environ Change 21 (4) 1262ndash1274
Kallstrom HN Ljung M 2005 Social sustainability and collaborative learningAmbio 34 376ndash382
Kelty R Kelty R 2011 Human dimensions of a 1047297shery at a crossroads resourcevaluation identity and way of life in a seasonal 1047297shing community Soc NatResour
24
(4)
334ndash348Klein RJT Nicholls RJ Thomalla F 2003 Resilience to natural hazards how
useful is this concept Environ Hazards 5 35ndash45
Krosnick
JA
Fabrigar
LR
1997
Designing
rating
scales
for
effective
measurementin surveys In Lyberg L Biemer P Collins M de Leeuw E Dippo C SchwarzN
Trewin
D
(Eds)
Survey
Measurement
and
Process
Quality
John
Wiley
andSons Inc New York NY pp 141ndash164
Leichenko R OrsquoBrien K 2008 Environmental Change and Globalization DoubleExposures Oxford University Press New York
Marschke M Berkes F 2006 Exploring Strategies that build livelihood resiliencea case from Cambodia Ecol Soc 11 (1) httpwwwecologyandsocietyorgvol11iss1art42
McGregor JA Cam1047297eld L Woodcock A 2009 Needs wants and goals wellbeingquality
of
life
and
public
policy
Appl
Res
Qual
Life
4
135ndash154McGregor JA 1994 Village credit and the reproduction of poverty in rural
Bangladesh In Acheson J (Ed) Economic Anthropology and the NewInstitutional Economics University Press of AmericaSociety for EconomicAnthropology Washington pp 261ndash281 (Chapter)
McGregor
JA
2011
Reimagining
development
through
the
crisis
watch
initiative
IDS Bull 42 (5) 17ndash23McLaughlin P Dietz T 2007 Structureagency and environment toward an
integrated perspective on vulnerability Glob Environ Change 39 (4) 99ndash111Meyer MA 2013 Social capital and resilience in the context of disaster social
capital
and
collective
ef 1047297cacy
for
disaster
resilience
connecting
individualswith communities and vulnerability with resilience in hurricane-pronecommunities in Florida PhD Dissertation Department of sociology Coloradostate University Fort Collins Colorado (311 p)
Mills DJ Adhuri D Phillips M Ravikumar B Padiyar AP 2011 Shocks recoverytrajectories and resilience among aquaculture-dependent households in post-tsunami
Aceh
Indonesia
Local
Environ
Int
J
Justice
Sustain
16
(5)
425ndash444Morduch J 1995 Income smoothing and consumption smoothing J Econ
Perspect 9 (3) 103ndash114Morris S Carletto C Hoddinott J Christiaensen L 2000 J Epidemiol Commun
Health 54 381ndash387Myers
RA
Worm
B
2003
Rapid
worldwide
depletion
of
predatory 1047297sh
communities Nature 423 280ndash283Nakagawa Y Shaw R 2004 Social capital a missing link to disaster recovery Int J
Mass
Emerg
Disasters
22
(1)
5ndash
34Nussbaum MC 2001 Adaptive preferences and womenrsquos options Econ Philos 1767ndash88
Oslashstergaard N Reenberg A 2010 Cultural barriers to climate change adaptation acase study from Northern Burkina Faso Glob Environ Change 20 (1) 142ndash152
OrsquoBrien K Leichenko R 2000 Double exposure assessing the impacts of climatechange within the context of economic globalization Glob Environ Change 10221ndash232
OrsquoBrien K Eriksen S Sygna L Naess LO 2006 Questioning complacencyclimate change impacts vulnerability and adaptation in Norway AMBIO JHum Environ 35 (2) 50ndash56
OrsquoBrien K Quilan T Ziervogel G 2009 Vulnerability interventions in the contextof multiple stressors lessons from the Southern Africa vulnerability initiative(SAVI) Environ Sci Policy 12 23ndash32
OrsquoRiordan T Jordan A 1999 Institutions climate change and cultural theorytowards a common analytical framework Glob Environ Change 9 (2) 81ndash93
Pain A Levine S 2012 A conceptual analysis of livelihoods and resilienceaddressing the
lsquoinsecurity of agency HPG Working Paper OverseasDevelopment Institute Humanitarian Policy Group London
Pauly D Christensen V Dalsgaard Froese JR Torres F 1998 Fishing downmarine food webs Science 279 (5352) 860ndash863
Pelling M Manuel-Navarrete D 2011 From resilience to transformation theadaptive cycle in two Mexican urban centersEcol Soc 16 (2)11 (online) httpwwwecologyandsocietyorgvol16iss2art11
Prowse
M
Scott
L
2008
Assets
and
adaptation
an
emerging
debate
IDS
Bull
39(4) 42ndash52
Putzel J 1997 Accounting for the lsquodark sidersquo of social capital reading Robert
Putnam
on
democracy
J
Int
Dev
9
(7)
939ndash949
Quinn CH Ziervogel G Taylor A Takama T Thomalla F 2011 Coping withmultiple
stresses
in
rural
South
Africa
Ecol
Soc
16
(3)
doihttpdxdoiorg105751ES-04216-160302
Reid P Vogel C 2006 Living and responding to multiple stressors in South Africamdashglimpses from KwaZulu-Natal Glob Environ Change 16 (2) 195ndash206
Roncoli C Ingram K Kirshen P 2001 The costs and risks of coping with droughtlivelihood
impacts
and
farmersrsquo
responses
in
Burkina
Faso
Clim
Res
19
119ndash132
Schwarz AM Beacuteneacute C Bennett G Boso D Hilly Z Paul C Posala R Sibiti SAndrew N 2011 Vulnerability and resilience of rural remote communities toshocks and global changes empirical analysis from the Solomon Islands GlobEnviron Change 21 1128ndash1140
Sinha
S
Lipton
M
Yaqub
S
2002
Poverty
and
damaging 1047298uctuations
how
dothey relate J Asian Afr Stud 37 (2) 186ndash243
Tansey J OrsquoRiordan T 1999 Cultural theory and risk a review Health Risk Soc 171ndash90
Teschl M Comim F 2005 Adaptive preferences and capabilities somepreliminary
conceptual
explorations
Rev
Soc
Econ
63
(2)
229ndash247
Trimble M Johnson D 2013 Artisanal 1047297shing as an undesirable way of life Theimplications for governance of 1047297shersrsquo wellbeing aspirations in coastal Uruguayand southeastern Brazil Mar Policy 37 37ndash44
Turner BL Kasperson RE Matson P McCarthy JJ Corell RW Christensen LEckley
N
Kasperson
JX
Luers
A
Martello
ML
Polsky
C
Pulsipher
ASchiller A 2003 A framework for vulnerability analysis in sustainabilityscience Proc Natl Acad Sci 100 (14) 8074ndash8079
Vigderhous G 1977 The level of measurement and
lsquoPermissiblersquo statistical analysisin social research Pac Sociol Rev 20 (1) 61ndash72
WFP 2013 Building Resilience Through Asset Creation Resilience and PreventionUnit
Policy
Programme
and
Innovation
Division
World
Food
Program
Rome(23 p)
Walker B Carpenter S Anderies J Abel N Cumming GS Janssen M Lebel LN J Peterson GD Pritchard R 2002 Resilience management in social-ecological systems a working hypothesis for a participatory approach ConservEcol
6
(1)
14Weber EU 2010 What shapes perceptions of climate change Clim Change 1 (3)
332ndash342
Wolf
J
Adger
WN
Lorenzoni
I
Abrahamson
V
Raine
R
2010
Social
capitalindividual responses to heat waves and climate change adaptation an empiricalstudy
of
two
UK
cities
Glob
Environ
Change
20
44ndash52Wood G 2003 Staying secure staying poor the Faustian bargain World Dev 31
(3) 455ndash471World Bank 2011 Building Resilience and Opportunities World Bankrsquos Social
Protection and Labour Strategy 2012ndash2022 World Bank Washington DCYamano T Alderman H Christiaensen L 2003 Child Growth Shocks and Food
Aid in Rural Ethiopia World Bank Washington DCZimmerman F Carter M 2003 Asset smoothing consumption smoothing and the
reproduction of inequality under risk and subsistence constraints J Dev Econ71 233ndash260
von Grebmer K Headey D Beacuteneacute C Haddad L et al 2013 Global Hunger IndexThe Challenge of Hunger Building Resilience to Achieve Food and NutritionSecurity Welthungerhilfe International Food Policy Research Institute andConcern Worldwide Bonn Washington DC and Dublin
170 C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
diversif non 1047297sher diversi1047297cation dummy 1 = yes
exit_1047297sh exit the 1047297shery sector dummy 1 = yes
migrat migrate dummy 1 = yes
quality of life indices
index_incom
income
index
ordinal
variable
coded
[-6
+6]
ndash6
=
very
poor
+6
=
very
strong
index_livelih livelihood index ordinal variable coded [-6 +6] ndash6 = very poor +6 = very strongindex_housing housing and infrastructure index ordinal variable coded [-6 +6] ndash6 = very poor +6 = very strong
index_educ education index ordinal variable coded [-6 +6]
ndash6 = very poor +6 = very strong
index_soc social capital index ordinal variable coded [-6 +6]
ndash6 = very poor +6 = very strong
index_health health index ordinal variable coded [-6 +6] ndash6 = very poor +6 = very strong
ind_emp empowerment index ordinal variable coded [-6 +6]
ndash6 = very poor +6 = very strong
index_soc_cris social capital index in time of crisis
ndash6 = very poor +6 = very strong
index_emp_cris empowerment index in time of crisis
ndash6 = very poor +6 = very strong
index_spirit index of spirituality
ordinal variable coded [-6 +6]
ndash6 = very poor +6 = very strong
household characteristics
HH head sex sex of household head dummy 1 = female
HH
head
age
age
of
household
head
age
in
years
HH head educ level of education of the household head 0 = no education 20 = post-graduate level
HH size size of household number of members (not adjusted for age)
log_asset household assets (log-transformed) value of household assets (proxy for wealth level)
community
resiliencecomm_recov level of recovery of the community
a Fitting a three level model requires two random-effect equations one for level three (country) and one for level two (community) with i = 1 nvc 1047297rst level of
observation (households) nested within k = 1 8 s level cluster (community) nested within j = 1 4 third level cluster (country)
162 C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
community level in the same way than the QoL indices that is by
averaging the scores obtained at the individual household level)
The best correlation was obtained with the QoL index of social
capital in time of crisis (R 2= 077 F = 0004) see Fig 6- suggesting
that communities with higher social capital in time of crisis are
also characterized by higher level of resilience
5 Discussion
Resilience has been increasingly recognized as a potentially
useful concept to help practitioners academics and policy-makers
better understand the links between shocks response and longer-
term development outcomes (Constas et al 2014a Beacuteneacute et al
2014) Incorporating resilience alongside vulnerability analysis can
contribute an essential element to societal ability to better prepare
for future shocks and stressors This paper argues that improving
our understanding of what contributes to or constitutes peoplersquos
resilience requires not only the development and
1047297eld-testing of
robust and measurable indices (Beacuteneacute 2013 Constas et al 2014b)
but also a better insight into the social factors including
knowledge perceptions and motivations- that in1047298uence and affect
individual and collective capacity to respond to shocks and
stressors
Our analysis conducted in eight 1047297shery-dependent communi-
ties from Fiji Ghana Sri Lanka and Vietnam reveals a series of
notable results in relation to these questions In considering these
outcomes it is important to 1047297rst take stock of potential limitations
pitfalls or biases in the study methodology Given the nature of the
1047297ndings two potential issues require further consideration First is
the question of how representative our sampling methodology
was It could be argued for instance that the observed low adoption
rates of non-1047297shery strategiesndash and in particular the low score of
the
lsquoexiting the
1047297sheryrsquo was driven by our sampling method
underrepresenting these groups as those who had effectively left
the 1047297shery were not included in the sample
The FGDs that preceded the household survey speci1047297cally
addressed this issue In Sri Lanka for instance the opening question
prompted participants (both men and women) to discuss whether
ldquo1047297shers in their community had ever left 1047297sheries due to their
inability to cope with adverse eventsrdquo The answer was that it
generally does not happen with the notable exception of someyoung
1047297shers who attempted to migrate to Australia through
illegal means If it occurred exiting the 1047297shery was said to be
temporary ldquothey may leave the village or 1047297shing but will come
back when the situation is favourablerdquo In Vietnam the sampling
was speci1047297cally designed to cover both
1047297shers and ex-1047297shers in
proportions represented in the community As a result 9 ex-1047297shers
were included in the sample Overall therefore although we were
unable to conceive of a completely representative sampling design
(in the statistical sense) the parallel information that was collected
in the FGDs and the individual households converge to suggest that
exiting the
1047297shery was not an option envisaged by the members of
these different communities and consequently that our sampling
was not too severely biased
0
2
4
6
8
10
12
14
16
-05 05 15 25
C o m m u n i t y l e v e l r e s i l i
e n c e i n d e x
Community level social capital in me of crisis
Fiji
Ghana
Sri Lanka
Vietnam
Fig 6 Correlation between social capital in time of crisis and resilience index
across the eight communities The straight line represents the linear relation
(R 2 = 077 F = 0004) and the bars are 95 con1047297dence intervals for each community
Random-effects parameters St Dev Std Err [95 Conf Interval]
country level
index_incom 043 024 0146 1266
index_livelih 051 027 0175 1464
index_housing 013 013 0018 0962
index_soc 039 024 0119 1303
index_soc_cris
078
038
0300
2009index_educ 015 013 0028 0834
const 090 067 0209 3861
community level
const 032 026 0066 1534
residuals 277 008 2617 2923
LR test vs linear regression chi2(7) = 3916 Prob gt chi2= 0000
p
lt 5
p
lt
1 p lt 1ma Fitting a three level model requires two random-effect equations one for level three (country) and one for level two (community) with i = 1 nvc 1047297rst level of
observation
(households)
nested
within
k
=
1
8
second
level
cluster
(community)
nested
within
j
=
1
4
third
level
cluster
(country)b The likelihood-ratio (LR) test comparing the nested mixed-effects model with the corresponding 1047297xed effect model con1047297rms the appropriate use of the mixed effect
model (chi2(7) = 3916 Prob gt chi2= 0000) and the Wald test con1047297rms that the independent variables are valid predictors (Wald chi2(45) = 59414 Prob gt chi2= 0000) A
speci1047297cation test performed on the 1047297xed effect model using a Pregibonrsquos goodness-of-link test shows good results (t = 077 P gt |t| = 0439)
c The dummy variables sev_event3 cat_event2 predict2 and comm_recov3 were omitted from the 1047297xed effect component for estimation purpose
Table 7 (Continued)
164 C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
The second potential limitation in our methodology relates to
the way the level of resilience of the households was assessed
While psychometric measurements are reliable and their results
replicable and testable when correctly implemented (Vigderhous
1977) one could fear that their use in the speci1047297c case of resilience
measurement could be subject to the effect of adaptive preference
that is the deliberate or re1047298exive process by which people adjust
their expectations and aspirations when trying to cope with
deterioration in living conditions (see eg Nussbaum 2001 Teschl
and Comim 2005) In our case this means that households
undergoing a degree of adaptive preference could have over-
estimated their ability to recover Although this risk is present we
tried to mitigate (or to reduce) it by introducing a qualifying
element in each of the coded answers of the resilience question-
naire so that respondents would have to associate the
1047297rst part of
their answer ldquoI have fully recoveredrdquo with a particular lsquoframe of
reference or quali1047297er (eg ldquoand it was not too dif 1047297cultrdquo) This frame
determined how they comprehend the questions being asked and
reduced the risk of the respondent simply relying on emotional
elements to answer these questions
Keeping in mind these potential limitations we now turn to
what we consider the most notable results of this research First is
the
lsquocumulative and continuous effect of shocks and stressors
whereby the impacts and disturbance of sequential shocksstressors and trends during the last 1047297ve years combine and
coalesce to create a constant non-stop stress We saw that the
nature and the source of events that were identi1047297ed by the
respondents in the four countries are all highly varied and
composite and reveal no speci1047297c clear pattern The events are a
combination of idiosyncratic and covariant sudden shocks and
long-term continuous trends Some are predictable while others
are totally unexpected All affect households simultaneously and
on an almost continuous basis The data suggests in particular that
on average households are hit by a new event every 16 months
This result calls into questions the framework generally used to
conduct shock or vulnerability assessment Often the approach has
been to disaggregate the problems people face and focus on single
threats such as eg 1047298ood or increase in food prices in order todevelop a clearer understanding of the impact of these particular
shocks and the ways people respond to them This approach has
been challenged however by a growing number of scholars who
argue that the reality households face on a daily basis is not linear
and mono-dimensional (OrsquoBrien and Leichenko 2000 Eriksen and
Silva 2009 Quinn et al 2011 McGregor 2011) Instead they argue
risks and vulnerability are often the product of multiple stressors
(Turner et al 2003 OrsquoBrien et al 2009) where social economic
political and biophysical factors interact combine and reinforce
each other to create a complex and dynamic multi-stressor multi-
shock environment (Reid and Vogel 2006 Adger 2006) Our
results corroborate this new interpretation
In line with this our analysis also shows that most households
engage in a suite of responses to a given shock On average
households adopted more than 4 types of responses to a particular
event This last result does not simply imply a rethinking of the way
shock or vulnerability assessments are conceptualized and
conducted see eg Turner et al (2003) or Leichenko and OrsquoBrien
(2008) It also demonstrates that the mental model (shock
gt response gt recovery) which is widely accepted in the
resilience literature is too simplistic and possibly misleading in
the sense that a state of (full) recovery may not exist This is at least
what was observed for the households included in our research
these households did not seem to have the chance or the time to
fully recover from one particular event before being affected by the
next Instead they were caught in what we could characterize as ldquoaconstant state of incomplete recoveringrdquo from new shocks and
stressors as illustrated in Fig 7
The next entry point in this discussion is wealth Our mixed
effect model (Table 7) shows that wealth was positively correlated
with household resilience Wealth has been identi1047297ed in the
literature as a key factor in strengthening the resilience of
households (Prowse and Scott 2008 WFP 2013) Analysis of
rural Ethiopian households hit by drought for instance showed that
while better-off households could sell livestock to smooth
consumption the poorer often tried to hold on to their livestock
at the expense of food consumption to preserve their options for
rebuilding herds The same study also shows that in the aftermath
of the hurricane Mitch in Honduras the relatively wealthy
households were able to rebuild their lost assets faster than thepoorest households for whom the effects of the hurricane were of
longer duration and felt much more acutely (Carter et al 2007) In
Fig 7 Left Current conceptualisation of resilience shock gt response gt recovery as presented in the literature [here redrawn from Carter et al 2007] Right actual
situation where the multi-stressor multi-shock environment induces that households are in a trajectory of continual and incomplete recovery Not represented here are the
multi-response
strategies
put
in
place
by
households
to
respond
to
these
adverse
events
C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170 165
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
disaster resilience National Disaster Resilience Roundtable Report 20September 2012 Melbourne Australia 36 p
Adger NW Dessai S Goulden M Hulme M Lorenzoni I Nelson DR Naess LO Wolf J Wreford A 2009 Are there social limits to adaptation to climatechange
Clim
Change
93
335ndash354Adger WN 2003 Social capital collective action and adaptation to climate
change Econ Geogr 79 (4) 387ndash404Adger WN 2006 Vulnerability Glob Environ Change 16 268ndash281Aldrich D 2010 Fixing recovery social capital in post-Crisis resilience J Homeland
Secur 6 1ndash10Ayers
J
Forsyth
T
2009
Community-based
adaptation
to
climate
changestrengthening resilience through development Environment 51 23ndash31
Beacuteneacute C Tew1047297k A 2001 Fishing effort allocation and 1047297shermenrsquos decision-makingprocess in a multi-species small-scale 1047297shery analysis of the conch and lobster1047297shery in Turks and Caicos Islands Hum Ecol 29 (2) 157ndash186
Beacuteneacute
C
Evans
L
Mills
D
Ovie
S
Raji
A
Ta1047297da
A
Kodio
A
Sinaba
F
Morand
PLemoalle J Andrew N 2011 Testing resilience thinking in a poverty contextexperience from the Niger river basin Glob Environ Change 21 (4) 1173ndash1184
Beacuteneacute C Godfrey-Wood R Newsham A Davies M2012 Resilience new utopia ornew tyranny
ndash Re1047298ection about the potentials and limits of the concept of
resilience
in
relation
to
vulnerability
reduction
programmes
IDS
Working
Paperno 405 Institute of Development Studies Brighton 61 p
Beacuteneacute C Newsham A Davies M Ulrichs M Godfrey-Wood R 2014 Resiliencepoverty and development J Int Dev 26 598ndash623
Beacuteneacute C Waid J Jackson-deGraffenried M Begum A Chowdhury M Skarin VRahman A Islam N Mamnun N Mainuddin K Shah MA 2015a Impact of climate-related
shocks
and
stresses
on
nutrition
and
food
security
in
ruralBangladesh Dhaka World Food Programme 119 p
Beacuteneacute C Frankenberger T Nelson S 2015b Design monitoring and evaluation of resilience interventions conceptual and empirical considerations IDS WorkingPaper no459 Institute of Development Studies 23 p
Beacuteneacute
C
2013
Towards
a
quanti1047297able
measure
of
resilience
IDS
Working
Paper
434Institute of Development Studies Brighton 27 p
Bandura A 1977 Self-ef 1047297cacy toward a unifying theory of behavioral changePsychol Rev 84 191ndash215
Baulch R Hoddinott J 2000 Economic mobility and poverty dynamics indeveloping countries J Dev Stud 36 (6) 1ndash23
Belhabib
D
Sumaila
UR
Pauly
D
2015
Feeding
the
poor
contribution
of
WestAfrican 1047297sheries to employment and food security Ocean Coast Manage 11172ndash81
Berkes F Folke C 1998 Linking social and ecological systems for resilience andsustainability In Berkes F Folke C (Eds) Linking Social and EcologicalSystems Management Practices and Social Mechanisms for Building ResilienceCambridge University Press Cambridge pp 1ndash25
Bernier Q Meinzen-Dick R 2014 Resilience and social capital Building Resiliencefor Food and Nutrition Security Conference Paper No 4 International FoodPolicy Research Institute Washington DC 26 p
Bhattamishra R Barrett C 2010 Community-Based risk managementarrangements a review World Dev 38 (7) 923ndash932
Boarini R Kolev A McGregor JA 2014 Measuring well-being and progress incountries at different stages of development towards a more universalconceptual framework OECD Working Paper No 235 Organisation forEconomic Co-operation and Development Development Center
ndash Better Life
Initiative Paris 59 p
Boyd E Osbahr H Ericksen P Tompkins E Carmen Lemos M Miller F 2008Resilience and
lsquoclimatizingrsquo development examples and policy implicationsDevelopment 51 390ndash396
Cam1047297eld
L
McGregor
JA
2005
Resilience
and
wellbeing
in
developing
countriesIn Ungar M (Ed) Handbook for Working with Children and Youth Pathwaysto Resilience Across Cultures and Contexts Sage Publications Thousand OaksCA
Cam1047297eld
L
Ruta
D
2007
Translation
is
not
enough
using
the
Global
PersonGenerated Index (GPGI) to assess individual quality of life in BangladeshThailand and Ethiopia Qual Life 16 (6) 1039ndash1051
Carter M Little P Mogues T Negatu W 2007 Poverty traps and natural disastersin Ethiopia and Honduras World Dev 35 (5) 835ndash856
Cleaver
F
2005
The
inequality
of
social
capital
and
the
reproduction
of
chronicpoverty World Dev 33 (6) 893ndash906
Constas M Frankenberger T Hoddinott J 2014a Resilience measurementprinciples toward an agenda for measurement design Resilience MeasurementTechnical Working Group Technical Series No 1 Food Security informationNetwork Rome
Constas MT Frankenberger J Hoddinott N Mock D Romano C Beacuteneacute DMaxwell 2014b A common analytical model for resilience measurementcausal framework and methodological options Food Security InformationNetwork (FSIN) Technical Series No 2 World Food Programme Rome
Coulthard S 2011 More than just access to 1047297sh the pros and cons of 1047297sherparticipation
in
a
customary
marine
tenure
(Padu)
system
under
pressure
MarPolicy 35 405ndash412
DFID 2011 De1047297ning Disaster Resilience A DFID Approach Paper Department forInternational Development London pp 20
Dercon S Hoddinott J Woldehanna T 2005 Shocks and consumption in 15ethiopian
villages
1999ndash2004
J
Afr
Econ
14
(4)
559ndash585Dercon S 1996 Risk crop choice and savings evidence from Tanzania Econ Dev
Cult Change 44 (3) 485ndash513Duit A Galaz V Eckerberg K 2010 Governance complexity and resilience Glob
Environ Change 20 (3) 363ndash368Eriksen
SEH
Silva
JA
2009
The
vulnerability
context
of
a
savannah
area
inMozambique household drought coping strategies and responses to economicchange Environ Sci Policy 12 (1) 33ndash52
Fafchamps M Lund S 2003 Risk-Sharing networks in rural Philippines J DevEcon 71 (2) 261ndash287
Frankenberger T Nelson S 2013 Background Paper for the Expert Consultation onResilience
Measurement
for
Food
Security
TANGO
International
Rome
Foodand Agricultural Organization and World Food Program
Heltberg R Siegel PS Jorgensen SL 2009 Addressing human vulnerability toclimate change towards a
lsquono-regretsrsquo approach Glob Environ Change 19 89ndash99
Hoddinott
J
Dercon
S
Krishnan
P
2009
Networks
and
informal
mutual
supportin 15 ethiopian villages a description In Kirsten JF Dorward AR Poulton CVink N (Eds) Institutional Economics Perspectives on African AgriculturalDevelopment International Food Policy Research Institute Washington DC pp273ndash286
Hoddinott
J
2006
Shocks
and
their
consequences
across
and
within
households
inRural Zimbabwe J Dev Stud 42 (2) 301ndash321
Intergovernmental Panel on Climate Change (IPCC) 2012 In Field CB Barros VStocker TF Qin D Dokken DJ Ebi KL Mastrandrea MD Mach KJPlattner G-K Allen SK Tignor MMidgley PM (Eds) Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation A SpecialReport of Working Groups I and II of the Intergovernmental Panel on ClimateChange Cambridge University Press Cambridge UK
Jackson T 2005 Motivating sustainable consumptionmdasha review of evidence onconsumer behaviour and behavioural change A Report to the Sustainable
Event type (Vietnam) Reduce
expenditures
Borrow
money
Reduce
Food
Change
1047297shing
strategy
Get
support
Increase
1047297shing
effort
Diversi1047297cation Seek new
collaboration
Migration Exit the
1047297shery
Sell
assets
Total
Others (aggregated) 4 7 4 6 3 0 1 3 0 0 2 30
Erosion 2 4 2 1 6 2 2 2 3 1 25
Catch reduced
suddenly
8 4 6 7 1 2 4 2 34
Gears lost 10 18 6 5 1 2 1 43
Cold wind prolongs 15 7 11 3 1 7 2 46
Typhoon
12
11
10
2
4
2
3
5
4
1
1
55
Illness
11 14
6
2
11
2
2
4
1
1
2
56Food price increase 20 17 19 2 8 5 1 72
Input price increase
continuously
47 39 33 21 40 5 6 16 1 208
Big boats compete
ground and catch
54 39 32 40 9 19 11 15 8 3 2 232
Catch
reduced
continuously
102
70
80
63
22
51
51
25
23
17
6
510
Total 285 230 209 152 105 91 87 75 39 23 15 1311
C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170 169
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
Development Research Network Centre for Environmental StrategiesUniversity of Surrey
Jones L Boyd E 2011 Exploring social barriers to adaptation insights fromWestern Nepal Glob Environ Change 21 (4) 1262ndash1274
Kallstrom HN Ljung M 2005 Social sustainability and collaborative learningAmbio 34 376ndash382
Kelty R Kelty R 2011 Human dimensions of a 1047297shery at a crossroads resourcevaluation identity and way of life in a seasonal 1047297shing community Soc NatResour
24
(4)
334ndash348Klein RJT Nicholls RJ Thomalla F 2003 Resilience to natural hazards how
useful is this concept Environ Hazards 5 35ndash45
Krosnick
JA
Fabrigar
LR
1997
Designing
rating
scales
for
effective
measurementin surveys In Lyberg L Biemer P Collins M de Leeuw E Dippo C SchwarzN
Trewin
D
(Eds)
Survey
Measurement
and
Process
Quality
John
Wiley
andSons Inc New York NY pp 141ndash164
Leichenko R OrsquoBrien K 2008 Environmental Change and Globalization DoubleExposures Oxford University Press New York
Marschke M Berkes F 2006 Exploring Strategies that build livelihood resiliencea case from Cambodia Ecol Soc 11 (1) httpwwwecologyandsocietyorgvol11iss1art42
McGregor JA Cam1047297eld L Woodcock A 2009 Needs wants and goals wellbeingquality
of
life
and
public
policy
Appl
Res
Qual
Life
4
135ndash154McGregor JA 1994 Village credit and the reproduction of poverty in rural
Bangladesh In Acheson J (Ed) Economic Anthropology and the NewInstitutional Economics University Press of AmericaSociety for EconomicAnthropology Washington pp 261ndash281 (Chapter)
McGregor
JA
2011
Reimagining
development
through
the
crisis
watch
initiative
IDS Bull 42 (5) 17ndash23McLaughlin P Dietz T 2007 Structureagency and environment toward an
integrated perspective on vulnerability Glob Environ Change 39 (4) 99ndash111Meyer MA 2013 Social capital and resilience in the context of disaster social
capital
and
collective
ef 1047297cacy
for
disaster
resilience
connecting
individualswith communities and vulnerability with resilience in hurricane-pronecommunities in Florida PhD Dissertation Department of sociology Coloradostate University Fort Collins Colorado (311 p)
Mills DJ Adhuri D Phillips M Ravikumar B Padiyar AP 2011 Shocks recoverytrajectories and resilience among aquaculture-dependent households in post-tsunami
Aceh
Indonesia
Local
Environ
Int
J
Justice
Sustain
16
(5)
425ndash444Morduch J 1995 Income smoothing and consumption smoothing J Econ
Perspect 9 (3) 103ndash114Morris S Carletto C Hoddinott J Christiaensen L 2000 J Epidemiol Commun
Health 54 381ndash387Myers
RA
Worm
B
2003
Rapid
worldwide
depletion
of
predatory 1047297sh
communities Nature 423 280ndash283Nakagawa Y Shaw R 2004 Social capital a missing link to disaster recovery Int J
Mass
Emerg
Disasters
22
(1)
5ndash
34Nussbaum MC 2001 Adaptive preferences and womenrsquos options Econ Philos 1767ndash88
Oslashstergaard N Reenberg A 2010 Cultural barriers to climate change adaptation acase study from Northern Burkina Faso Glob Environ Change 20 (1) 142ndash152
OrsquoBrien K Leichenko R 2000 Double exposure assessing the impacts of climatechange within the context of economic globalization Glob Environ Change 10221ndash232
OrsquoBrien K Eriksen S Sygna L Naess LO 2006 Questioning complacencyclimate change impacts vulnerability and adaptation in Norway AMBIO JHum Environ 35 (2) 50ndash56
OrsquoBrien K Quilan T Ziervogel G 2009 Vulnerability interventions in the contextof multiple stressors lessons from the Southern Africa vulnerability initiative(SAVI) Environ Sci Policy 12 23ndash32
OrsquoRiordan T Jordan A 1999 Institutions climate change and cultural theorytowards a common analytical framework Glob Environ Change 9 (2) 81ndash93
Pain A Levine S 2012 A conceptual analysis of livelihoods and resilienceaddressing the
lsquoinsecurity of agency HPG Working Paper OverseasDevelopment Institute Humanitarian Policy Group London
Pauly D Christensen V Dalsgaard Froese JR Torres F 1998 Fishing downmarine food webs Science 279 (5352) 860ndash863
Pelling M Manuel-Navarrete D 2011 From resilience to transformation theadaptive cycle in two Mexican urban centersEcol Soc 16 (2)11 (online) httpwwwecologyandsocietyorgvol16iss2art11
Prowse
M
Scott
L
2008
Assets
and
adaptation
an
emerging
debate
IDS
Bull
39(4) 42ndash52
Putzel J 1997 Accounting for the lsquodark sidersquo of social capital reading Robert
Putnam
on
democracy
J
Int
Dev
9
(7)
939ndash949
Quinn CH Ziervogel G Taylor A Takama T Thomalla F 2011 Coping withmultiple
stresses
in
rural
South
Africa
Ecol
Soc
16
(3)
doihttpdxdoiorg105751ES-04216-160302
Reid P Vogel C 2006 Living and responding to multiple stressors in South Africamdashglimpses from KwaZulu-Natal Glob Environ Change 16 (2) 195ndash206
Roncoli C Ingram K Kirshen P 2001 The costs and risks of coping with droughtlivelihood
impacts
and
farmersrsquo
responses
in
Burkina
Faso
Clim
Res
19
119ndash132
Schwarz AM Beacuteneacute C Bennett G Boso D Hilly Z Paul C Posala R Sibiti SAndrew N 2011 Vulnerability and resilience of rural remote communities toshocks and global changes empirical analysis from the Solomon Islands GlobEnviron Change 21 1128ndash1140
Sinha
S
Lipton
M
Yaqub
S
2002
Poverty
and
damaging 1047298uctuations
how
dothey relate J Asian Afr Stud 37 (2) 186ndash243
Tansey J OrsquoRiordan T 1999 Cultural theory and risk a review Health Risk Soc 171ndash90
Teschl M Comim F 2005 Adaptive preferences and capabilities somepreliminary
conceptual
explorations
Rev
Soc
Econ
63
(2)
229ndash247
Trimble M Johnson D 2013 Artisanal 1047297shing as an undesirable way of life Theimplications for governance of 1047297shersrsquo wellbeing aspirations in coastal Uruguayand southeastern Brazil Mar Policy 37 37ndash44
Turner BL Kasperson RE Matson P McCarthy JJ Corell RW Christensen LEckley
N
Kasperson
JX
Luers
A
Martello
ML
Polsky
C
Pulsipher
ASchiller A 2003 A framework for vulnerability analysis in sustainabilityscience Proc Natl Acad Sci 100 (14) 8074ndash8079
Vigderhous G 1977 The level of measurement and
lsquoPermissiblersquo statistical analysisin social research Pac Sociol Rev 20 (1) 61ndash72
WFP 2013 Building Resilience Through Asset Creation Resilience and PreventionUnit
Policy
Programme
and
Innovation
Division
World
Food
Program
Rome(23 p)
Walker B Carpenter S Anderies J Abel N Cumming GS Janssen M Lebel LN J Peterson GD Pritchard R 2002 Resilience management in social-ecological systems a working hypothesis for a participatory approach ConservEcol
6
(1)
14Weber EU 2010 What shapes perceptions of climate change Clim Change 1 (3)
332ndash342
Wolf
J
Adger
WN
Lorenzoni
I
Abrahamson
V
Raine
R
2010
Social
capitalindividual responses to heat waves and climate change adaptation an empiricalstudy
of
two
UK
cities
Glob
Environ
Change
20
44ndash52Wood G 2003 Staying secure staying poor the Faustian bargain World Dev 31
(3) 455ndash471World Bank 2011 Building Resilience and Opportunities World Bankrsquos Social
Protection and Labour Strategy 2012ndash2022 World Bank Washington DCYamano T Alderman H Christiaensen L 2003 Child Growth Shocks and Food
Aid in Rural Ethiopia World Bank Washington DCZimmerman F Carter M 2003 Asset smoothing consumption smoothing and the
reproduction of inequality under risk and subsistence constraints J Dev Econ71 233ndash260
von Grebmer K Headey D Beacuteneacute C Haddad L et al 2013 Global Hunger IndexThe Challenge of Hunger Building Resilience to Achieve Food and NutritionSecurity Welthungerhilfe International Food Policy Research Institute andConcern Worldwide Bonn Washington DC and Dublin
170 C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
community level in the same way than the QoL indices that is by
averaging the scores obtained at the individual household level)
The best correlation was obtained with the QoL index of social
capital in time of crisis (R 2= 077 F = 0004) see Fig 6- suggesting
that communities with higher social capital in time of crisis are
also characterized by higher level of resilience
5 Discussion
Resilience has been increasingly recognized as a potentially
useful concept to help practitioners academics and policy-makers
better understand the links between shocks response and longer-
term development outcomes (Constas et al 2014a Beacuteneacute et al
2014) Incorporating resilience alongside vulnerability analysis can
contribute an essential element to societal ability to better prepare
for future shocks and stressors This paper argues that improving
our understanding of what contributes to or constitutes peoplersquos
resilience requires not only the development and
1047297eld-testing of
robust and measurable indices (Beacuteneacute 2013 Constas et al 2014b)
but also a better insight into the social factors including
knowledge perceptions and motivations- that in1047298uence and affect
individual and collective capacity to respond to shocks and
stressors
Our analysis conducted in eight 1047297shery-dependent communi-
ties from Fiji Ghana Sri Lanka and Vietnam reveals a series of
notable results in relation to these questions In considering these
outcomes it is important to 1047297rst take stock of potential limitations
pitfalls or biases in the study methodology Given the nature of the
1047297ndings two potential issues require further consideration First is
the question of how representative our sampling methodology
was It could be argued for instance that the observed low adoption
rates of non-1047297shery strategiesndash and in particular the low score of
the
lsquoexiting the
1047297sheryrsquo was driven by our sampling method
underrepresenting these groups as those who had effectively left
the 1047297shery were not included in the sample
The FGDs that preceded the household survey speci1047297cally
addressed this issue In Sri Lanka for instance the opening question
prompted participants (both men and women) to discuss whether
ldquo1047297shers in their community had ever left 1047297sheries due to their
inability to cope with adverse eventsrdquo The answer was that it
generally does not happen with the notable exception of someyoung
1047297shers who attempted to migrate to Australia through
illegal means If it occurred exiting the 1047297shery was said to be
temporary ldquothey may leave the village or 1047297shing but will come
back when the situation is favourablerdquo In Vietnam the sampling
was speci1047297cally designed to cover both
1047297shers and ex-1047297shers in
proportions represented in the community As a result 9 ex-1047297shers
were included in the sample Overall therefore although we were
unable to conceive of a completely representative sampling design
(in the statistical sense) the parallel information that was collected
in the FGDs and the individual households converge to suggest that
exiting the
1047297shery was not an option envisaged by the members of
these different communities and consequently that our sampling
was not too severely biased
0
2
4
6
8
10
12
14
16
-05 05 15 25
C o m m u n i t y l e v e l r e s i l i
e n c e i n d e x
Community level social capital in me of crisis
Fiji
Ghana
Sri Lanka
Vietnam
Fig 6 Correlation between social capital in time of crisis and resilience index
across the eight communities The straight line represents the linear relation
(R 2 = 077 F = 0004) and the bars are 95 con1047297dence intervals for each community
Random-effects parameters St Dev Std Err [95 Conf Interval]
country level
index_incom 043 024 0146 1266
index_livelih 051 027 0175 1464
index_housing 013 013 0018 0962
index_soc 039 024 0119 1303
index_soc_cris
078
038
0300
2009index_educ 015 013 0028 0834
const 090 067 0209 3861
community level
const 032 026 0066 1534
residuals 277 008 2617 2923
LR test vs linear regression chi2(7) = 3916 Prob gt chi2= 0000
p
lt 5
p
lt
1 p lt 1ma Fitting a three level model requires two random-effect equations one for level three (country) and one for level two (community) with i = 1 nvc 1047297rst level of
observation
(households)
nested
within
k
=
1
8
second
level
cluster
(community)
nested
within
j
=
1
4
third
level
cluster
(country)b The likelihood-ratio (LR) test comparing the nested mixed-effects model with the corresponding 1047297xed effect model con1047297rms the appropriate use of the mixed effect
model (chi2(7) = 3916 Prob gt chi2= 0000) and the Wald test con1047297rms that the independent variables are valid predictors (Wald chi2(45) = 59414 Prob gt chi2= 0000) A
speci1047297cation test performed on the 1047297xed effect model using a Pregibonrsquos goodness-of-link test shows good results (t = 077 P gt |t| = 0439)
c The dummy variables sev_event3 cat_event2 predict2 and comm_recov3 were omitted from the 1047297xed effect component for estimation purpose
Table 7 (Continued)
164 C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
The second potential limitation in our methodology relates to
the way the level of resilience of the households was assessed
While psychometric measurements are reliable and their results
replicable and testable when correctly implemented (Vigderhous
1977) one could fear that their use in the speci1047297c case of resilience
measurement could be subject to the effect of adaptive preference
that is the deliberate or re1047298exive process by which people adjust
their expectations and aspirations when trying to cope with
deterioration in living conditions (see eg Nussbaum 2001 Teschl
and Comim 2005) In our case this means that households
undergoing a degree of adaptive preference could have over-
estimated their ability to recover Although this risk is present we
tried to mitigate (or to reduce) it by introducing a qualifying
element in each of the coded answers of the resilience question-
naire so that respondents would have to associate the
1047297rst part of
their answer ldquoI have fully recoveredrdquo with a particular lsquoframe of
reference or quali1047297er (eg ldquoand it was not too dif 1047297cultrdquo) This frame
determined how they comprehend the questions being asked and
reduced the risk of the respondent simply relying on emotional
elements to answer these questions
Keeping in mind these potential limitations we now turn to
what we consider the most notable results of this research First is
the
lsquocumulative and continuous effect of shocks and stressors
whereby the impacts and disturbance of sequential shocksstressors and trends during the last 1047297ve years combine and
coalesce to create a constant non-stop stress We saw that the
nature and the source of events that were identi1047297ed by the
respondents in the four countries are all highly varied and
composite and reveal no speci1047297c clear pattern The events are a
combination of idiosyncratic and covariant sudden shocks and
long-term continuous trends Some are predictable while others
are totally unexpected All affect households simultaneously and
on an almost continuous basis The data suggests in particular that
on average households are hit by a new event every 16 months
This result calls into questions the framework generally used to
conduct shock or vulnerability assessment Often the approach has
been to disaggregate the problems people face and focus on single
threats such as eg 1047298ood or increase in food prices in order todevelop a clearer understanding of the impact of these particular
shocks and the ways people respond to them This approach has
been challenged however by a growing number of scholars who
argue that the reality households face on a daily basis is not linear
and mono-dimensional (OrsquoBrien and Leichenko 2000 Eriksen and
Silva 2009 Quinn et al 2011 McGregor 2011) Instead they argue
risks and vulnerability are often the product of multiple stressors
(Turner et al 2003 OrsquoBrien et al 2009) where social economic
political and biophysical factors interact combine and reinforce
each other to create a complex and dynamic multi-stressor multi-
shock environment (Reid and Vogel 2006 Adger 2006) Our
results corroborate this new interpretation
In line with this our analysis also shows that most households
engage in a suite of responses to a given shock On average
households adopted more than 4 types of responses to a particular
event This last result does not simply imply a rethinking of the way
shock or vulnerability assessments are conceptualized and
conducted see eg Turner et al (2003) or Leichenko and OrsquoBrien
(2008) It also demonstrates that the mental model (shock
gt response gt recovery) which is widely accepted in the
resilience literature is too simplistic and possibly misleading in
the sense that a state of (full) recovery may not exist This is at least
what was observed for the households included in our research
these households did not seem to have the chance or the time to
fully recover from one particular event before being affected by the
next Instead they were caught in what we could characterize as ldquoaconstant state of incomplete recoveringrdquo from new shocks and
stressors as illustrated in Fig 7
The next entry point in this discussion is wealth Our mixed
effect model (Table 7) shows that wealth was positively correlated
with household resilience Wealth has been identi1047297ed in the
literature as a key factor in strengthening the resilience of
households (Prowse and Scott 2008 WFP 2013) Analysis of
rural Ethiopian households hit by drought for instance showed that
while better-off households could sell livestock to smooth
consumption the poorer often tried to hold on to their livestock
at the expense of food consumption to preserve their options for
rebuilding herds The same study also shows that in the aftermath
of the hurricane Mitch in Honduras the relatively wealthy
households were able to rebuild their lost assets faster than thepoorest households for whom the effects of the hurricane were of
longer duration and felt much more acutely (Carter et al 2007) In
Fig 7 Left Current conceptualisation of resilience shock gt response gt recovery as presented in the literature [here redrawn from Carter et al 2007] Right actual
situation where the multi-stressor multi-shock environment induces that households are in a trajectory of continual and incomplete recovery Not represented here are the
multi-response
strategies
put
in
place
by
households
to
respond
to
these
adverse
events
C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170 165
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
disaster resilience National Disaster Resilience Roundtable Report 20September 2012 Melbourne Australia 36 p
Adger NW Dessai S Goulden M Hulme M Lorenzoni I Nelson DR Naess LO Wolf J Wreford A 2009 Are there social limits to adaptation to climatechange
Clim
Change
93
335ndash354Adger WN 2003 Social capital collective action and adaptation to climate
change Econ Geogr 79 (4) 387ndash404Adger WN 2006 Vulnerability Glob Environ Change 16 268ndash281Aldrich D 2010 Fixing recovery social capital in post-Crisis resilience J Homeland
Secur 6 1ndash10Ayers
J
Forsyth
T
2009
Community-based
adaptation
to
climate
changestrengthening resilience through development Environment 51 23ndash31
Beacuteneacute C Tew1047297k A 2001 Fishing effort allocation and 1047297shermenrsquos decision-makingprocess in a multi-species small-scale 1047297shery analysis of the conch and lobster1047297shery in Turks and Caicos Islands Hum Ecol 29 (2) 157ndash186
Beacuteneacute
C
Evans
L
Mills
D
Ovie
S
Raji
A
Ta1047297da
A
Kodio
A
Sinaba
F
Morand
PLemoalle J Andrew N 2011 Testing resilience thinking in a poverty contextexperience from the Niger river basin Glob Environ Change 21 (4) 1173ndash1184
Beacuteneacute C Godfrey-Wood R Newsham A Davies M2012 Resilience new utopia ornew tyranny
ndash Re1047298ection about the potentials and limits of the concept of
resilience
in
relation
to
vulnerability
reduction
programmes
IDS
Working
Paperno 405 Institute of Development Studies Brighton 61 p
Beacuteneacute C Newsham A Davies M Ulrichs M Godfrey-Wood R 2014 Resiliencepoverty and development J Int Dev 26 598ndash623
Beacuteneacute C Waid J Jackson-deGraffenried M Begum A Chowdhury M Skarin VRahman A Islam N Mamnun N Mainuddin K Shah MA 2015a Impact of climate-related
shocks
and
stresses
on
nutrition
and
food
security
in
ruralBangladesh Dhaka World Food Programme 119 p
Beacuteneacute C Frankenberger T Nelson S 2015b Design monitoring and evaluation of resilience interventions conceptual and empirical considerations IDS WorkingPaper no459 Institute of Development Studies 23 p
Beacuteneacute
C
2013
Towards
a
quanti1047297able
measure
of
resilience
IDS
Working
Paper
434Institute of Development Studies Brighton 27 p
Bandura A 1977 Self-ef 1047297cacy toward a unifying theory of behavioral changePsychol Rev 84 191ndash215
Baulch R Hoddinott J 2000 Economic mobility and poverty dynamics indeveloping countries J Dev Stud 36 (6) 1ndash23
Belhabib
D
Sumaila
UR
Pauly
D
2015
Feeding
the
poor
contribution
of
WestAfrican 1047297sheries to employment and food security Ocean Coast Manage 11172ndash81
Berkes F Folke C 1998 Linking social and ecological systems for resilience andsustainability In Berkes F Folke C (Eds) Linking Social and EcologicalSystems Management Practices and Social Mechanisms for Building ResilienceCambridge University Press Cambridge pp 1ndash25
Bernier Q Meinzen-Dick R 2014 Resilience and social capital Building Resiliencefor Food and Nutrition Security Conference Paper No 4 International FoodPolicy Research Institute Washington DC 26 p
Bhattamishra R Barrett C 2010 Community-Based risk managementarrangements a review World Dev 38 (7) 923ndash932
Boarini R Kolev A McGregor JA 2014 Measuring well-being and progress incountries at different stages of development towards a more universalconceptual framework OECD Working Paper No 235 Organisation forEconomic Co-operation and Development Development Center
ndash Better Life
Initiative Paris 59 p
Boyd E Osbahr H Ericksen P Tompkins E Carmen Lemos M Miller F 2008Resilience and
lsquoclimatizingrsquo development examples and policy implicationsDevelopment 51 390ndash396
Cam1047297eld
L
McGregor
JA
2005
Resilience
and
wellbeing
in
developing
countriesIn Ungar M (Ed) Handbook for Working with Children and Youth Pathwaysto Resilience Across Cultures and Contexts Sage Publications Thousand OaksCA
Cam1047297eld
L
Ruta
D
2007
Translation
is
not
enough
using
the
Global
PersonGenerated Index (GPGI) to assess individual quality of life in BangladeshThailand and Ethiopia Qual Life 16 (6) 1039ndash1051
Carter M Little P Mogues T Negatu W 2007 Poverty traps and natural disastersin Ethiopia and Honduras World Dev 35 (5) 835ndash856
Cleaver
F
2005
The
inequality
of
social
capital
and
the
reproduction
of
chronicpoverty World Dev 33 (6) 893ndash906
Constas M Frankenberger T Hoddinott J 2014a Resilience measurementprinciples toward an agenda for measurement design Resilience MeasurementTechnical Working Group Technical Series No 1 Food Security informationNetwork Rome
Constas MT Frankenberger J Hoddinott N Mock D Romano C Beacuteneacute DMaxwell 2014b A common analytical model for resilience measurementcausal framework and methodological options Food Security InformationNetwork (FSIN) Technical Series No 2 World Food Programme Rome
Coulthard S 2011 More than just access to 1047297sh the pros and cons of 1047297sherparticipation
in
a
customary
marine
tenure
(Padu)
system
under
pressure
MarPolicy 35 405ndash412
DFID 2011 De1047297ning Disaster Resilience A DFID Approach Paper Department forInternational Development London pp 20
Dercon S Hoddinott J Woldehanna T 2005 Shocks and consumption in 15ethiopian
villages
1999ndash2004
J
Afr
Econ
14
(4)
559ndash585Dercon S 1996 Risk crop choice and savings evidence from Tanzania Econ Dev
Cult Change 44 (3) 485ndash513Duit A Galaz V Eckerberg K 2010 Governance complexity and resilience Glob
Environ Change 20 (3) 363ndash368Eriksen
SEH
Silva
JA
2009
The
vulnerability
context
of
a
savannah
area
inMozambique household drought coping strategies and responses to economicchange Environ Sci Policy 12 (1) 33ndash52
Fafchamps M Lund S 2003 Risk-Sharing networks in rural Philippines J DevEcon 71 (2) 261ndash287
Frankenberger T Nelson S 2013 Background Paper for the Expert Consultation onResilience
Measurement
for
Food
Security
TANGO
International
Rome
Foodand Agricultural Organization and World Food Program
Heltberg R Siegel PS Jorgensen SL 2009 Addressing human vulnerability toclimate change towards a
lsquono-regretsrsquo approach Glob Environ Change 19 89ndash99
Hoddinott
J
Dercon
S
Krishnan
P
2009
Networks
and
informal
mutual
supportin 15 ethiopian villages a description In Kirsten JF Dorward AR Poulton CVink N (Eds) Institutional Economics Perspectives on African AgriculturalDevelopment International Food Policy Research Institute Washington DC pp273ndash286
Hoddinott
J
2006
Shocks
and
their
consequences
across
and
within
households
inRural Zimbabwe J Dev Stud 42 (2) 301ndash321
Intergovernmental Panel on Climate Change (IPCC) 2012 In Field CB Barros VStocker TF Qin D Dokken DJ Ebi KL Mastrandrea MD Mach KJPlattner G-K Allen SK Tignor MMidgley PM (Eds) Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation A SpecialReport of Working Groups I and II of the Intergovernmental Panel on ClimateChange Cambridge University Press Cambridge UK
Jackson T 2005 Motivating sustainable consumptionmdasha review of evidence onconsumer behaviour and behavioural change A Report to the Sustainable
Event type (Vietnam) Reduce
expenditures
Borrow
money
Reduce
Food
Change
1047297shing
strategy
Get
support
Increase
1047297shing
effort
Diversi1047297cation Seek new
collaboration
Migration Exit the
1047297shery
Sell
assets
Total
Others (aggregated) 4 7 4 6 3 0 1 3 0 0 2 30
Erosion 2 4 2 1 6 2 2 2 3 1 25
Catch reduced
suddenly
8 4 6 7 1 2 4 2 34
Gears lost 10 18 6 5 1 2 1 43
Cold wind prolongs 15 7 11 3 1 7 2 46
Typhoon
12
11
10
2
4
2
3
5
4
1
1
55
Illness
11 14
6
2
11
2
2
4
1
1
2
56Food price increase 20 17 19 2 8 5 1 72
Input price increase
continuously
47 39 33 21 40 5 6 16 1 208
Big boats compete
ground and catch
54 39 32 40 9 19 11 15 8 3 2 232
Catch
reduced
continuously
102
70
80
63
22
51
51
25
23
17
6
510
Total 285 230 209 152 105 91 87 75 39 23 15 1311
C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170 169
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
Development Research Network Centre for Environmental StrategiesUniversity of Surrey
Jones L Boyd E 2011 Exploring social barriers to adaptation insights fromWestern Nepal Glob Environ Change 21 (4) 1262ndash1274
Kallstrom HN Ljung M 2005 Social sustainability and collaborative learningAmbio 34 376ndash382
Kelty R Kelty R 2011 Human dimensions of a 1047297shery at a crossroads resourcevaluation identity and way of life in a seasonal 1047297shing community Soc NatResour
24
(4)
334ndash348Klein RJT Nicholls RJ Thomalla F 2003 Resilience to natural hazards how
useful is this concept Environ Hazards 5 35ndash45
Krosnick
JA
Fabrigar
LR
1997
Designing
rating
scales
for
effective
measurementin surveys In Lyberg L Biemer P Collins M de Leeuw E Dippo C SchwarzN
Trewin
D
(Eds)
Survey
Measurement
and
Process
Quality
John
Wiley
andSons Inc New York NY pp 141ndash164
Leichenko R OrsquoBrien K 2008 Environmental Change and Globalization DoubleExposures Oxford University Press New York
Marschke M Berkes F 2006 Exploring Strategies that build livelihood resiliencea case from Cambodia Ecol Soc 11 (1) httpwwwecologyandsocietyorgvol11iss1art42
McGregor JA Cam1047297eld L Woodcock A 2009 Needs wants and goals wellbeingquality
of
life
and
public
policy
Appl
Res
Qual
Life
4
135ndash154McGregor JA 1994 Village credit and the reproduction of poverty in rural
Bangladesh In Acheson J (Ed) Economic Anthropology and the NewInstitutional Economics University Press of AmericaSociety for EconomicAnthropology Washington pp 261ndash281 (Chapter)
McGregor
JA
2011
Reimagining
development
through
the
crisis
watch
initiative
IDS Bull 42 (5) 17ndash23McLaughlin P Dietz T 2007 Structureagency and environment toward an
integrated perspective on vulnerability Glob Environ Change 39 (4) 99ndash111Meyer MA 2013 Social capital and resilience in the context of disaster social
capital
and
collective
ef 1047297cacy
for
disaster
resilience
connecting
individualswith communities and vulnerability with resilience in hurricane-pronecommunities in Florida PhD Dissertation Department of sociology Coloradostate University Fort Collins Colorado (311 p)
Mills DJ Adhuri D Phillips M Ravikumar B Padiyar AP 2011 Shocks recoverytrajectories and resilience among aquaculture-dependent households in post-tsunami
Aceh
Indonesia
Local
Environ
Int
J
Justice
Sustain
16
(5)
425ndash444Morduch J 1995 Income smoothing and consumption smoothing J Econ
Perspect 9 (3) 103ndash114Morris S Carletto C Hoddinott J Christiaensen L 2000 J Epidemiol Commun
Health 54 381ndash387Myers
RA
Worm
B
2003
Rapid
worldwide
depletion
of
predatory 1047297sh
communities Nature 423 280ndash283Nakagawa Y Shaw R 2004 Social capital a missing link to disaster recovery Int J
Mass
Emerg
Disasters
22
(1)
5ndash
34Nussbaum MC 2001 Adaptive preferences and womenrsquos options Econ Philos 1767ndash88
Oslashstergaard N Reenberg A 2010 Cultural barriers to climate change adaptation acase study from Northern Burkina Faso Glob Environ Change 20 (1) 142ndash152
OrsquoBrien K Leichenko R 2000 Double exposure assessing the impacts of climatechange within the context of economic globalization Glob Environ Change 10221ndash232
OrsquoBrien K Eriksen S Sygna L Naess LO 2006 Questioning complacencyclimate change impacts vulnerability and adaptation in Norway AMBIO JHum Environ 35 (2) 50ndash56
OrsquoBrien K Quilan T Ziervogel G 2009 Vulnerability interventions in the contextof multiple stressors lessons from the Southern Africa vulnerability initiative(SAVI) Environ Sci Policy 12 23ndash32
OrsquoRiordan T Jordan A 1999 Institutions climate change and cultural theorytowards a common analytical framework Glob Environ Change 9 (2) 81ndash93
Pain A Levine S 2012 A conceptual analysis of livelihoods and resilienceaddressing the
lsquoinsecurity of agency HPG Working Paper OverseasDevelopment Institute Humanitarian Policy Group London
Pauly D Christensen V Dalsgaard Froese JR Torres F 1998 Fishing downmarine food webs Science 279 (5352) 860ndash863
Pelling M Manuel-Navarrete D 2011 From resilience to transformation theadaptive cycle in two Mexican urban centersEcol Soc 16 (2)11 (online) httpwwwecologyandsocietyorgvol16iss2art11
Prowse
M
Scott
L
2008
Assets
and
adaptation
an
emerging
debate
IDS
Bull
39(4) 42ndash52
Putzel J 1997 Accounting for the lsquodark sidersquo of social capital reading Robert
Putnam
on
democracy
J
Int
Dev
9
(7)
939ndash949
Quinn CH Ziervogel G Taylor A Takama T Thomalla F 2011 Coping withmultiple
stresses
in
rural
South
Africa
Ecol
Soc
16
(3)
doihttpdxdoiorg105751ES-04216-160302
Reid P Vogel C 2006 Living and responding to multiple stressors in South Africamdashglimpses from KwaZulu-Natal Glob Environ Change 16 (2) 195ndash206
Roncoli C Ingram K Kirshen P 2001 The costs and risks of coping with droughtlivelihood
impacts
and
farmersrsquo
responses
in
Burkina
Faso
Clim
Res
19
119ndash132
Schwarz AM Beacuteneacute C Bennett G Boso D Hilly Z Paul C Posala R Sibiti SAndrew N 2011 Vulnerability and resilience of rural remote communities toshocks and global changes empirical analysis from the Solomon Islands GlobEnviron Change 21 1128ndash1140
Sinha
S
Lipton
M
Yaqub
S
2002
Poverty
and
damaging 1047298uctuations
how
dothey relate J Asian Afr Stud 37 (2) 186ndash243
Tansey J OrsquoRiordan T 1999 Cultural theory and risk a review Health Risk Soc 171ndash90
Teschl M Comim F 2005 Adaptive preferences and capabilities somepreliminary
conceptual
explorations
Rev
Soc
Econ
63
(2)
229ndash247
Trimble M Johnson D 2013 Artisanal 1047297shing as an undesirable way of life Theimplications for governance of 1047297shersrsquo wellbeing aspirations in coastal Uruguayand southeastern Brazil Mar Policy 37 37ndash44
Turner BL Kasperson RE Matson P McCarthy JJ Corell RW Christensen LEckley
N
Kasperson
JX
Luers
A
Martello
ML
Polsky
C
Pulsipher
ASchiller A 2003 A framework for vulnerability analysis in sustainabilityscience Proc Natl Acad Sci 100 (14) 8074ndash8079
Vigderhous G 1977 The level of measurement and
lsquoPermissiblersquo statistical analysisin social research Pac Sociol Rev 20 (1) 61ndash72
WFP 2013 Building Resilience Through Asset Creation Resilience and PreventionUnit
Policy
Programme
and
Innovation
Division
World
Food
Program
Rome(23 p)
Walker B Carpenter S Anderies J Abel N Cumming GS Janssen M Lebel LN J Peterson GD Pritchard R 2002 Resilience management in social-ecological systems a working hypothesis for a participatory approach ConservEcol
6
(1)
14Weber EU 2010 What shapes perceptions of climate change Clim Change 1 (3)
332ndash342
Wolf
J
Adger
WN
Lorenzoni
I
Abrahamson
V
Raine
R
2010
Social
capitalindividual responses to heat waves and climate change adaptation an empiricalstudy
of
two
UK
cities
Glob
Environ
Change
20
44ndash52Wood G 2003 Staying secure staying poor the Faustian bargain World Dev 31
(3) 455ndash471World Bank 2011 Building Resilience and Opportunities World Bankrsquos Social
Protection and Labour Strategy 2012ndash2022 World Bank Washington DCYamano T Alderman H Christiaensen L 2003 Child Growth Shocks and Food
Aid in Rural Ethiopia World Bank Washington DCZimmerman F Carter M 2003 Asset smoothing consumption smoothing and the
reproduction of inequality under risk and subsistence constraints J Dev Econ71 233ndash260
von Grebmer K Headey D Beacuteneacute C Haddad L et al 2013 Global Hunger IndexThe Challenge of Hunger Building Resilience to Achieve Food and NutritionSecurity Welthungerhilfe International Food Policy Research Institute andConcern Worldwide Bonn Washington DC and Dublin
170 C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
community level in the same way than the QoL indices that is by
averaging the scores obtained at the individual household level)
The best correlation was obtained with the QoL index of social
capital in time of crisis (R 2= 077 F = 0004) see Fig 6- suggesting
that communities with higher social capital in time of crisis are
also characterized by higher level of resilience
5 Discussion
Resilience has been increasingly recognized as a potentially
useful concept to help practitioners academics and policy-makers
better understand the links between shocks response and longer-
term development outcomes (Constas et al 2014a Beacuteneacute et al
2014) Incorporating resilience alongside vulnerability analysis can
contribute an essential element to societal ability to better prepare
for future shocks and stressors This paper argues that improving
our understanding of what contributes to or constitutes peoplersquos
resilience requires not only the development and
1047297eld-testing of
robust and measurable indices (Beacuteneacute 2013 Constas et al 2014b)
but also a better insight into the social factors including
knowledge perceptions and motivations- that in1047298uence and affect
individual and collective capacity to respond to shocks and
stressors
Our analysis conducted in eight 1047297shery-dependent communi-
ties from Fiji Ghana Sri Lanka and Vietnam reveals a series of
notable results in relation to these questions In considering these
outcomes it is important to 1047297rst take stock of potential limitations
pitfalls or biases in the study methodology Given the nature of the
1047297ndings two potential issues require further consideration First is
the question of how representative our sampling methodology
was It could be argued for instance that the observed low adoption
rates of non-1047297shery strategiesndash and in particular the low score of
the
lsquoexiting the
1047297sheryrsquo was driven by our sampling method
underrepresenting these groups as those who had effectively left
the 1047297shery were not included in the sample
The FGDs that preceded the household survey speci1047297cally
addressed this issue In Sri Lanka for instance the opening question
prompted participants (both men and women) to discuss whether
ldquo1047297shers in their community had ever left 1047297sheries due to their
inability to cope with adverse eventsrdquo The answer was that it
generally does not happen with the notable exception of someyoung
1047297shers who attempted to migrate to Australia through
illegal means If it occurred exiting the 1047297shery was said to be
temporary ldquothey may leave the village or 1047297shing but will come
back when the situation is favourablerdquo In Vietnam the sampling
was speci1047297cally designed to cover both
1047297shers and ex-1047297shers in
proportions represented in the community As a result 9 ex-1047297shers
were included in the sample Overall therefore although we were
unable to conceive of a completely representative sampling design
(in the statistical sense) the parallel information that was collected
in the FGDs and the individual households converge to suggest that
exiting the
1047297shery was not an option envisaged by the members of
these different communities and consequently that our sampling
was not too severely biased
0
2
4
6
8
10
12
14
16
-05 05 15 25
C o m m u n i t y l e v e l r e s i l i
e n c e i n d e x
Community level social capital in me of crisis
Fiji
Ghana
Sri Lanka
Vietnam
Fig 6 Correlation between social capital in time of crisis and resilience index
across the eight communities The straight line represents the linear relation
(R 2 = 077 F = 0004) and the bars are 95 con1047297dence intervals for each community
Random-effects parameters St Dev Std Err [95 Conf Interval]
country level
index_incom 043 024 0146 1266
index_livelih 051 027 0175 1464
index_housing 013 013 0018 0962
index_soc 039 024 0119 1303
index_soc_cris
078
038
0300
2009index_educ 015 013 0028 0834
const 090 067 0209 3861
community level
const 032 026 0066 1534
residuals 277 008 2617 2923
LR test vs linear regression chi2(7) = 3916 Prob gt chi2= 0000
p
lt 5
p
lt
1 p lt 1ma Fitting a three level model requires two random-effect equations one for level three (country) and one for level two (community) with i = 1 nvc 1047297rst level of
observation
(households)
nested
within
k
=
1
8
second
level
cluster
(community)
nested
within
j
=
1
4
third
level
cluster
(country)b The likelihood-ratio (LR) test comparing the nested mixed-effects model with the corresponding 1047297xed effect model con1047297rms the appropriate use of the mixed effect
model (chi2(7) = 3916 Prob gt chi2= 0000) and the Wald test con1047297rms that the independent variables are valid predictors (Wald chi2(45) = 59414 Prob gt chi2= 0000) A
speci1047297cation test performed on the 1047297xed effect model using a Pregibonrsquos goodness-of-link test shows good results (t = 077 P gt |t| = 0439)
c The dummy variables sev_event3 cat_event2 predict2 and comm_recov3 were omitted from the 1047297xed effect component for estimation purpose
Table 7 (Continued)
164 C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
The second potential limitation in our methodology relates to
the way the level of resilience of the households was assessed
While psychometric measurements are reliable and their results
replicable and testable when correctly implemented (Vigderhous
1977) one could fear that their use in the speci1047297c case of resilience
measurement could be subject to the effect of adaptive preference
that is the deliberate or re1047298exive process by which people adjust
their expectations and aspirations when trying to cope with
deterioration in living conditions (see eg Nussbaum 2001 Teschl
and Comim 2005) In our case this means that households
undergoing a degree of adaptive preference could have over-
estimated their ability to recover Although this risk is present we
tried to mitigate (or to reduce) it by introducing a qualifying
element in each of the coded answers of the resilience question-
naire so that respondents would have to associate the
1047297rst part of
their answer ldquoI have fully recoveredrdquo with a particular lsquoframe of
reference or quali1047297er (eg ldquoand it was not too dif 1047297cultrdquo) This frame
determined how they comprehend the questions being asked and
reduced the risk of the respondent simply relying on emotional
elements to answer these questions
Keeping in mind these potential limitations we now turn to
what we consider the most notable results of this research First is
the
lsquocumulative and continuous effect of shocks and stressors
whereby the impacts and disturbance of sequential shocksstressors and trends during the last 1047297ve years combine and
coalesce to create a constant non-stop stress We saw that the
nature and the source of events that were identi1047297ed by the
respondents in the four countries are all highly varied and
composite and reveal no speci1047297c clear pattern The events are a
combination of idiosyncratic and covariant sudden shocks and
long-term continuous trends Some are predictable while others
are totally unexpected All affect households simultaneously and
on an almost continuous basis The data suggests in particular that
on average households are hit by a new event every 16 months
This result calls into questions the framework generally used to
conduct shock or vulnerability assessment Often the approach has
been to disaggregate the problems people face and focus on single
threats such as eg 1047298ood or increase in food prices in order todevelop a clearer understanding of the impact of these particular
shocks and the ways people respond to them This approach has
been challenged however by a growing number of scholars who
argue that the reality households face on a daily basis is not linear
and mono-dimensional (OrsquoBrien and Leichenko 2000 Eriksen and
Silva 2009 Quinn et al 2011 McGregor 2011) Instead they argue
risks and vulnerability are often the product of multiple stressors
(Turner et al 2003 OrsquoBrien et al 2009) where social economic
political and biophysical factors interact combine and reinforce
each other to create a complex and dynamic multi-stressor multi-
shock environment (Reid and Vogel 2006 Adger 2006) Our
results corroborate this new interpretation
In line with this our analysis also shows that most households
engage in a suite of responses to a given shock On average
households adopted more than 4 types of responses to a particular
event This last result does not simply imply a rethinking of the way
shock or vulnerability assessments are conceptualized and
conducted see eg Turner et al (2003) or Leichenko and OrsquoBrien
(2008) It also demonstrates that the mental model (shock
gt response gt recovery) which is widely accepted in the
resilience literature is too simplistic and possibly misleading in
the sense that a state of (full) recovery may not exist This is at least
what was observed for the households included in our research
these households did not seem to have the chance or the time to
fully recover from one particular event before being affected by the
next Instead they were caught in what we could characterize as ldquoaconstant state of incomplete recoveringrdquo from new shocks and
stressors as illustrated in Fig 7
The next entry point in this discussion is wealth Our mixed
effect model (Table 7) shows that wealth was positively correlated
with household resilience Wealth has been identi1047297ed in the
literature as a key factor in strengthening the resilience of
households (Prowse and Scott 2008 WFP 2013) Analysis of
rural Ethiopian households hit by drought for instance showed that
while better-off households could sell livestock to smooth
consumption the poorer often tried to hold on to their livestock
at the expense of food consumption to preserve their options for
rebuilding herds The same study also shows that in the aftermath
of the hurricane Mitch in Honduras the relatively wealthy
households were able to rebuild their lost assets faster than thepoorest households for whom the effects of the hurricane were of
longer duration and felt much more acutely (Carter et al 2007) In
Fig 7 Left Current conceptualisation of resilience shock gt response gt recovery as presented in the literature [here redrawn from Carter et al 2007] Right actual
situation where the multi-stressor multi-shock environment induces that households are in a trajectory of continual and incomplete recovery Not represented here are the
multi-response
strategies
put
in
place
by
households
to
respond
to
these
adverse
events
C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170 165
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
disaster resilience National Disaster Resilience Roundtable Report 20September 2012 Melbourne Australia 36 p
Adger NW Dessai S Goulden M Hulme M Lorenzoni I Nelson DR Naess LO Wolf J Wreford A 2009 Are there social limits to adaptation to climatechange
Clim
Change
93
335ndash354Adger WN 2003 Social capital collective action and adaptation to climate
change Econ Geogr 79 (4) 387ndash404Adger WN 2006 Vulnerability Glob Environ Change 16 268ndash281Aldrich D 2010 Fixing recovery social capital in post-Crisis resilience J Homeland
Secur 6 1ndash10Ayers
J
Forsyth
T
2009
Community-based
adaptation
to
climate
changestrengthening resilience through development Environment 51 23ndash31
Beacuteneacute C Tew1047297k A 2001 Fishing effort allocation and 1047297shermenrsquos decision-makingprocess in a multi-species small-scale 1047297shery analysis of the conch and lobster1047297shery in Turks and Caicos Islands Hum Ecol 29 (2) 157ndash186
Beacuteneacute
C
Evans
L
Mills
D
Ovie
S
Raji
A
Ta1047297da
A
Kodio
A
Sinaba
F
Morand
PLemoalle J Andrew N 2011 Testing resilience thinking in a poverty contextexperience from the Niger river basin Glob Environ Change 21 (4) 1173ndash1184
Beacuteneacute C Godfrey-Wood R Newsham A Davies M2012 Resilience new utopia ornew tyranny
ndash Re1047298ection about the potentials and limits of the concept of
resilience
in
relation
to
vulnerability
reduction
programmes
IDS
Working
Paperno 405 Institute of Development Studies Brighton 61 p
Beacuteneacute C Newsham A Davies M Ulrichs M Godfrey-Wood R 2014 Resiliencepoverty and development J Int Dev 26 598ndash623
Beacuteneacute C Waid J Jackson-deGraffenried M Begum A Chowdhury M Skarin VRahman A Islam N Mamnun N Mainuddin K Shah MA 2015a Impact of climate-related
shocks
and
stresses
on
nutrition
and
food
security
in
ruralBangladesh Dhaka World Food Programme 119 p
Beacuteneacute C Frankenberger T Nelson S 2015b Design monitoring and evaluation of resilience interventions conceptual and empirical considerations IDS WorkingPaper no459 Institute of Development Studies 23 p
Beacuteneacute
C
2013
Towards
a
quanti1047297able
measure
of
resilience
IDS
Working
Paper
434Institute of Development Studies Brighton 27 p
Bandura A 1977 Self-ef 1047297cacy toward a unifying theory of behavioral changePsychol Rev 84 191ndash215
Baulch R Hoddinott J 2000 Economic mobility and poverty dynamics indeveloping countries J Dev Stud 36 (6) 1ndash23
Belhabib
D
Sumaila
UR
Pauly
D
2015
Feeding
the
poor
contribution
of
WestAfrican 1047297sheries to employment and food security Ocean Coast Manage 11172ndash81
Berkes F Folke C 1998 Linking social and ecological systems for resilience andsustainability In Berkes F Folke C (Eds) Linking Social and EcologicalSystems Management Practices and Social Mechanisms for Building ResilienceCambridge University Press Cambridge pp 1ndash25
Bernier Q Meinzen-Dick R 2014 Resilience and social capital Building Resiliencefor Food and Nutrition Security Conference Paper No 4 International FoodPolicy Research Institute Washington DC 26 p
Bhattamishra R Barrett C 2010 Community-Based risk managementarrangements a review World Dev 38 (7) 923ndash932
Boarini R Kolev A McGregor JA 2014 Measuring well-being and progress incountries at different stages of development towards a more universalconceptual framework OECD Working Paper No 235 Organisation forEconomic Co-operation and Development Development Center
ndash Better Life
Initiative Paris 59 p
Boyd E Osbahr H Ericksen P Tompkins E Carmen Lemos M Miller F 2008Resilience and
lsquoclimatizingrsquo development examples and policy implicationsDevelopment 51 390ndash396
Cam1047297eld
L
McGregor
JA
2005
Resilience
and
wellbeing
in
developing
countriesIn Ungar M (Ed) Handbook for Working with Children and Youth Pathwaysto Resilience Across Cultures and Contexts Sage Publications Thousand OaksCA
Cam1047297eld
L
Ruta
D
2007
Translation
is
not
enough
using
the
Global
PersonGenerated Index (GPGI) to assess individual quality of life in BangladeshThailand and Ethiopia Qual Life 16 (6) 1039ndash1051
Carter M Little P Mogues T Negatu W 2007 Poverty traps and natural disastersin Ethiopia and Honduras World Dev 35 (5) 835ndash856
Cleaver
F
2005
The
inequality
of
social
capital
and
the
reproduction
of
chronicpoverty World Dev 33 (6) 893ndash906
Constas M Frankenberger T Hoddinott J 2014a Resilience measurementprinciples toward an agenda for measurement design Resilience MeasurementTechnical Working Group Technical Series No 1 Food Security informationNetwork Rome
Constas MT Frankenberger J Hoddinott N Mock D Romano C Beacuteneacute DMaxwell 2014b A common analytical model for resilience measurementcausal framework and methodological options Food Security InformationNetwork (FSIN) Technical Series No 2 World Food Programme Rome
Coulthard S 2011 More than just access to 1047297sh the pros and cons of 1047297sherparticipation
in
a
customary
marine
tenure
(Padu)
system
under
pressure
MarPolicy 35 405ndash412
DFID 2011 De1047297ning Disaster Resilience A DFID Approach Paper Department forInternational Development London pp 20
Dercon S Hoddinott J Woldehanna T 2005 Shocks and consumption in 15ethiopian
villages
1999ndash2004
J
Afr
Econ
14
(4)
559ndash585Dercon S 1996 Risk crop choice and savings evidence from Tanzania Econ Dev
Cult Change 44 (3) 485ndash513Duit A Galaz V Eckerberg K 2010 Governance complexity and resilience Glob
Environ Change 20 (3) 363ndash368Eriksen
SEH
Silva
JA
2009
The
vulnerability
context
of
a
savannah
area
inMozambique household drought coping strategies and responses to economicchange Environ Sci Policy 12 (1) 33ndash52
Fafchamps M Lund S 2003 Risk-Sharing networks in rural Philippines J DevEcon 71 (2) 261ndash287
Frankenberger T Nelson S 2013 Background Paper for the Expert Consultation onResilience
Measurement
for
Food
Security
TANGO
International
Rome
Foodand Agricultural Organization and World Food Program
Heltberg R Siegel PS Jorgensen SL 2009 Addressing human vulnerability toclimate change towards a
lsquono-regretsrsquo approach Glob Environ Change 19 89ndash99
Hoddinott
J
Dercon
S
Krishnan
P
2009
Networks
and
informal
mutual
supportin 15 ethiopian villages a description In Kirsten JF Dorward AR Poulton CVink N (Eds) Institutional Economics Perspectives on African AgriculturalDevelopment International Food Policy Research Institute Washington DC pp273ndash286
Hoddinott
J
2006
Shocks
and
their
consequences
across
and
within
households
inRural Zimbabwe J Dev Stud 42 (2) 301ndash321
Intergovernmental Panel on Climate Change (IPCC) 2012 In Field CB Barros VStocker TF Qin D Dokken DJ Ebi KL Mastrandrea MD Mach KJPlattner G-K Allen SK Tignor MMidgley PM (Eds) Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation A SpecialReport of Working Groups I and II of the Intergovernmental Panel on ClimateChange Cambridge University Press Cambridge UK
Jackson T 2005 Motivating sustainable consumptionmdasha review of evidence onconsumer behaviour and behavioural change A Report to the Sustainable
Event type (Vietnam) Reduce
expenditures
Borrow
money
Reduce
Food
Change
1047297shing
strategy
Get
support
Increase
1047297shing
effort
Diversi1047297cation Seek new
collaboration
Migration Exit the
1047297shery
Sell
assets
Total
Others (aggregated) 4 7 4 6 3 0 1 3 0 0 2 30
Erosion 2 4 2 1 6 2 2 2 3 1 25
Catch reduced
suddenly
8 4 6 7 1 2 4 2 34
Gears lost 10 18 6 5 1 2 1 43
Cold wind prolongs 15 7 11 3 1 7 2 46
Typhoon
12
11
10
2
4
2
3
5
4
1
1
55
Illness
11 14
6
2
11
2
2
4
1
1
2
56Food price increase 20 17 19 2 8 5 1 72
Input price increase
continuously
47 39 33 21 40 5 6 16 1 208
Big boats compete
ground and catch
54 39 32 40 9 19 11 15 8 3 2 232
Catch
reduced
continuously
102
70
80
63
22
51
51
25
23
17
6
510
Total 285 230 209 152 105 91 87 75 39 23 15 1311
C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170 169
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
Development Research Network Centre for Environmental StrategiesUniversity of Surrey
Jones L Boyd E 2011 Exploring social barriers to adaptation insights fromWestern Nepal Glob Environ Change 21 (4) 1262ndash1274
Kallstrom HN Ljung M 2005 Social sustainability and collaborative learningAmbio 34 376ndash382
Kelty R Kelty R 2011 Human dimensions of a 1047297shery at a crossroads resourcevaluation identity and way of life in a seasonal 1047297shing community Soc NatResour
24
(4)
334ndash348Klein RJT Nicholls RJ Thomalla F 2003 Resilience to natural hazards how
useful is this concept Environ Hazards 5 35ndash45
Krosnick
JA
Fabrigar
LR
1997
Designing
rating
scales
for
effective
measurementin surveys In Lyberg L Biemer P Collins M de Leeuw E Dippo C SchwarzN
Trewin
D
(Eds)
Survey
Measurement
and
Process
Quality
John
Wiley
andSons Inc New York NY pp 141ndash164
Leichenko R OrsquoBrien K 2008 Environmental Change and Globalization DoubleExposures Oxford University Press New York
Marschke M Berkes F 2006 Exploring Strategies that build livelihood resiliencea case from Cambodia Ecol Soc 11 (1) httpwwwecologyandsocietyorgvol11iss1art42
McGregor JA Cam1047297eld L Woodcock A 2009 Needs wants and goals wellbeingquality
of
life
and
public
policy
Appl
Res
Qual
Life
4
135ndash154McGregor JA 1994 Village credit and the reproduction of poverty in rural
Bangladesh In Acheson J (Ed) Economic Anthropology and the NewInstitutional Economics University Press of AmericaSociety for EconomicAnthropology Washington pp 261ndash281 (Chapter)
McGregor
JA
2011
Reimagining
development
through
the
crisis
watch
initiative
IDS Bull 42 (5) 17ndash23McLaughlin P Dietz T 2007 Structureagency and environment toward an
integrated perspective on vulnerability Glob Environ Change 39 (4) 99ndash111Meyer MA 2013 Social capital and resilience in the context of disaster social
capital
and
collective
ef 1047297cacy
for
disaster
resilience
connecting
individualswith communities and vulnerability with resilience in hurricane-pronecommunities in Florida PhD Dissertation Department of sociology Coloradostate University Fort Collins Colorado (311 p)
Mills DJ Adhuri D Phillips M Ravikumar B Padiyar AP 2011 Shocks recoverytrajectories and resilience among aquaculture-dependent households in post-tsunami
Aceh
Indonesia
Local
Environ
Int
J
Justice
Sustain
16
(5)
425ndash444Morduch J 1995 Income smoothing and consumption smoothing J Econ
Perspect 9 (3) 103ndash114Morris S Carletto C Hoddinott J Christiaensen L 2000 J Epidemiol Commun
Health 54 381ndash387Myers
RA
Worm
B
2003
Rapid
worldwide
depletion
of
predatory 1047297sh
communities Nature 423 280ndash283Nakagawa Y Shaw R 2004 Social capital a missing link to disaster recovery Int J
Mass
Emerg
Disasters
22
(1)
5ndash
34Nussbaum MC 2001 Adaptive preferences and womenrsquos options Econ Philos 1767ndash88
Oslashstergaard N Reenberg A 2010 Cultural barriers to climate change adaptation acase study from Northern Burkina Faso Glob Environ Change 20 (1) 142ndash152
OrsquoBrien K Leichenko R 2000 Double exposure assessing the impacts of climatechange within the context of economic globalization Glob Environ Change 10221ndash232
OrsquoBrien K Eriksen S Sygna L Naess LO 2006 Questioning complacencyclimate change impacts vulnerability and adaptation in Norway AMBIO JHum Environ 35 (2) 50ndash56
OrsquoBrien K Quilan T Ziervogel G 2009 Vulnerability interventions in the contextof multiple stressors lessons from the Southern Africa vulnerability initiative(SAVI) Environ Sci Policy 12 23ndash32
OrsquoRiordan T Jordan A 1999 Institutions climate change and cultural theorytowards a common analytical framework Glob Environ Change 9 (2) 81ndash93
Pain A Levine S 2012 A conceptual analysis of livelihoods and resilienceaddressing the
lsquoinsecurity of agency HPG Working Paper OverseasDevelopment Institute Humanitarian Policy Group London
Pauly D Christensen V Dalsgaard Froese JR Torres F 1998 Fishing downmarine food webs Science 279 (5352) 860ndash863
Pelling M Manuel-Navarrete D 2011 From resilience to transformation theadaptive cycle in two Mexican urban centersEcol Soc 16 (2)11 (online) httpwwwecologyandsocietyorgvol16iss2art11
Prowse
M
Scott
L
2008
Assets
and
adaptation
an
emerging
debate
IDS
Bull
39(4) 42ndash52
Putzel J 1997 Accounting for the lsquodark sidersquo of social capital reading Robert
Putnam
on
democracy
J
Int
Dev
9
(7)
939ndash949
Quinn CH Ziervogel G Taylor A Takama T Thomalla F 2011 Coping withmultiple
stresses
in
rural
South
Africa
Ecol
Soc
16
(3)
doihttpdxdoiorg105751ES-04216-160302
Reid P Vogel C 2006 Living and responding to multiple stressors in South Africamdashglimpses from KwaZulu-Natal Glob Environ Change 16 (2) 195ndash206
Roncoli C Ingram K Kirshen P 2001 The costs and risks of coping with droughtlivelihood
impacts
and
farmersrsquo
responses
in
Burkina
Faso
Clim
Res
19
119ndash132
Schwarz AM Beacuteneacute C Bennett G Boso D Hilly Z Paul C Posala R Sibiti SAndrew N 2011 Vulnerability and resilience of rural remote communities toshocks and global changes empirical analysis from the Solomon Islands GlobEnviron Change 21 1128ndash1140
Sinha
S
Lipton
M
Yaqub
S
2002
Poverty
and
damaging 1047298uctuations
how
dothey relate J Asian Afr Stud 37 (2) 186ndash243
Tansey J OrsquoRiordan T 1999 Cultural theory and risk a review Health Risk Soc 171ndash90
Teschl M Comim F 2005 Adaptive preferences and capabilities somepreliminary
conceptual
explorations
Rev
Soc
Econ
63
(2)
229ndash247
Trimble M Johnson D 2013 Artisanal 1047297shing as an undesirable way of life Theimplications for governance of 1047297shersrsquo wellbeing aspirations in coastal Uruguayand southeastern Brazil Mar Policy 37 37ndash44
Turner BL Kasperson RE Matson P McCarthy JJ Corell RW Christensen LEckley
N
Kasperson
JX
Luers
A
Martello
ML
Polsky
C
Pulsipher
ASchiller A 2003 A framework for vulnerability analysis in sustainabilityscience Proc Natl Acad Sci 100 (14) 8074ndash8079
Vigderhous G 1977 The level of measurement and
lsquoPermissiblersquo statistical analysisin social research Pac Sociol Rev 20 (1) 61ndash72
WFP 2013 Building Resilience Through Asset Creation Resilience and PreventionUnit
Policy
Programme
and
Innovation
Division
World
Food
Program
Rome(23 p)
Walker B Carpenter S Anderies J Abel N Cumming GS Janssen M Lebel LN J Peterson GD Pritchard R 2002 Resilience management in social-ecological systems a working hypothesis for a participatory approach ConservEcol
6
(1)
14Weber EU 2010 What shapes perceptions of climate change Clim Change 1 (3)
332ndash342
Wolf
J
Adger
WN
Lorenzoni
I
Abrahamson
V
Raine
R
2010
Social
capitalindividual responses to heat waves and climate change adaptation an empiricalstudy
of
two
UK
cities
Glob
Environ
Change
20
44ndash52Wood G 2003 Staying secure staying poor the Faustian bargain World Dev 31
(3) 455ndash471World Bank 2011 Building Resilience and Opportunities World Bankrsquos Social
Protection and Labour Strategy 2012ndash2022 World Bank Washington DCYamano T Alderman H Christiaensen L 2003 Child Growth Shocks and Food
Aid in Rural Ethiopia World Bank Washington DCZimmerman F Carter M 2003 Asset smoothing consumption smoothing and the
reproduction of inequality under risk and subsistence constraints J Dev Econ71 233ndash260
von Grebmer K Headey D Beacuteneacute C Haddad L et al 2013 Global Hunger IndexThe Challenge of Hunger Building Resilience to Achieve Food and NutritionSecurity Welthungerhilfe International Food Policy Research Institute andConcern Worldwide Bonn Washington DC and Dublin
170 C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
The second potential limitation in our methodology relates to
the way the level of resilience of the households was assessed
While psychometric measurements are reliable and their results
replicable and testable when correctly implemented (Vigderhous
1977) one could fear that their use in the speci1047297c case of resilience
measurement could be subject to the effect of adaptive preference
that is the deliberate or re1047298exive process by which people adjust
their expectations and aspirations when trying to cope with
deterioration in living conditions (see eg Nussbaum 2001 Teschl
and Comim 2005) In our case this means that households
undergoing a degree of adaptive preference could have over-
estimated their ability to recover Although this risk is present we
tried to mitigate (or to reduce) it by introducing a qualifying
element in each of the coded answers of the resilience question-
naire so that respondents would have to associate the
1047297rst part of
their answer ldquoI have fully recoveredrdquo with a particular lsquoframe of
reference or quali1047297er (eg ldquoand it was not too dif 1047297cultrdquo) This frame
determined how they comprehend the questions being asked and
reduced the risk of the respondent simply relying on emotional
elements to answer these questions
Keeping in mind these potential limitations we now turn to
what we consider the most notable results of this research First is
the
lsquocumulative and continuous effect of shocks and stressors
whereby the impacts and disturbance of sequential shocksstressors and trends during the last 1047297ve years combine and
coalesce to create a constant non-stop stress We saw that the
nature and the source of events that were identi1047297ed by the
respondents in the four countries are all highly varied and
composite and reveal no speci1047297c clear pattern The events are a
combination of idiosyncratic and covariant sudden shocks and
long-term continuous trends Some are predictable while others
are totally unexpected All affect households simultaneously and
on an almost continuous basis The data suggests in particular that
on average households are hit by a new event every 16 months
This result calls into questions the framework generally used to
conduct shock or vulnerability assessment Often the approach has
been to disaggregate the problems people face and focus on single
threats such as eg 1047298ood or increase in food prices in order todevelop a clearer understanding of the impact of these particular
shocks and the ways people respond to them This approach has
been challenged however by a growing number of scholars who
argue that the reality households face on a daily basis is not linear
and mono-dimensional (OrsquoBrien and Leichenko 2000 Eriksen and
Silva 2009 Quinn et al 2011 McGregor 2011) Instead they argue
risks and vulnerability are often the product of multiple stressors
(Turner et al 2003 OrsquoBrien et al 2009) where social economic
political and biophysical factors interact combine and reinforce
each other to create a complex and dynamic multi-stressor multi-
shock environment (Reid and Vogel 2006 Adger 2006) Our
results corroborate this new interpretation
In line with this our analysis also shows that most households
engage in a suite of responses to a given shock On average
households adopted more than 4 types of responses to a particular
event This last result does not simply imply a rethinking of the way
shock or vulnerability assessments are conceptualized and
conducted see eg Turner et al (2003) or Leichenko and OrsquoBrien
(2008) It also demonstrates that the mental model (shock
gt response gt recovery) which is widely accepted in the
resilience literature is too simplistic and possibly misleading in
the sense that a state of (full) recovery may not exist This is at least
what was observed for the households included in our research
these households did not seem to have the chance or the time to
fully recover from one particular event before being affected by the
next Instead they were caught in what we could characterize as ldquoaconstant state of incomplete recoveringrdquo from new shocks and
stressors as illustrated in Fig 7
The next entry point in this discussion is wealth Our mixed
effect model (Table 7) shows that wealth was positively correlated
with household resilience Wealth has been identi1047297ed in the
literature as a key factor in strengthening the resilience of
households (Prowse and Scott 2008 WFP 2013) Analysis of
rural Ethiopian households hit by drought for instance showed that
while better-off households could sell livestock to smooth
consumption the poorer often tried to hold on to their livestock
at the expense of food consumption to preserve their options for
rebuilding herds The same study also shows that in the aftermath
of the hurricane Mitch in Honduras the relatively wealthy
households were able to rebuild their lost assets faster than thepoorest households for whom the effects of the hurricane were of
longer duration and felt much more acutely (Carter et al 2007) In
Fig 7 Left Current conceptualisation of resilience shock gt response gt recovery as presented in the literature [here redrawn from Carter et al 2007] Right actual
situation where the multi-stressor multi-shock environment induces that households are in a trajectory of continual and incomplete recovery Not represented here are the
multi-response
strategies
put
in
place
by
households
to
respond
to
these
adverse
events
C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170 165
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
disaster resilience National Disaster Resilience Roundtable Report 20September 2012 Melbourne Australia 36 p
Adger NW Dessai S Goulden M Hulme M Lorenzoni I Nelson DR Naess LO Wolf J Wreford A 2009 Are there social limits to adaptation to climatechange
Clim
Change
93
335ndash354Adger WN 2003 Social capital collective action and adaptation to climate
change Econ Geogr 79 (4) 387ndash404Adger WN 2006 Vulnerability Glob Environ Change 16 268ndash281Aldrich D 2010 Fixing recovery social capital in post-Crisis resilience J Homeland
Secur 6 1ndash10Ayers
J
Forsyth
T
2009
Community-based
adaptation
to
climate
changestrengthening resilience through development Environment 51 23ndash31
Beacuteneacute C Tew1047297k A 2001 Fishing effort allocation and 1047297shermenrsquos decision-makingprocess in a multi-species small-scale 1047297shery analysis of the conch and lobster1047297shery in Turks and Caicos Islands Hum Ecol 29 (2) 157ndash186
Beacuteneacute
C
Evans
L
Mills
D
Ovie
S
Raji
A
Ta1047297da
A
Kodio
A
Sinaba
F
Morand
PLemoalle J Andrew N 2011 Testing resilience thinking in a poverty contextexperience from the Niger river basin Glob Environ Change 21 (4) 1173ndash1184
Beacuteneacute C Godfrey-Wood R Newsham A Davies M2012 Resilience new utopia ornew tyranny
ndash Re1047298ection about the potentials and limits of the concept of
resilience
in
relation
to
vulnerability
reduction
programmes
IDS
Working
Paperno 405 Institute of Development Studies Brighton 61 p
Beacuteneacute C Newsham A Davies M Ulrichs M Godfrey-Wood R 2014 Resiliencepoverty and development J Int Dev 26 598ndash623
Beacuteneacute C Waid J Jackson-deGraffenried M Begum A Chowdhury M Skarin VRahman A Islam N Mamnun N Mainuddin K Shah MA 2015a Impact of climate-related
shocks
and
stresses
on
nutrition
and
food
security
in
ruralBangladesh Dhaka World Food Programme 119 p
Beacuteneacute C Frankenberger T Nelson S 2015b Design monitoring and evaluation of resilience interventions conceptual and empirical considerations IDS WorkingPaper no459 Institute of Development Studies 23 p
Beacuteneacute
C
2013
Towards
a
quanti1047297able
measure
of
resilience
IDS
Working
Paper
434Institute of Development Studies Brighton 27 p
Bandura A 1977 Self-ef 1047297cacy toward a unifying theory of behavioral changePsychol Rev 84 191ndash215
Baulch R Hoddinott J 2000 Economic mobility and poverty dynamics indeveloping countries J Dev Stud 36 (6) 1ndash23
Belhabib
D
Sumaila
UR
Pauly
D
2015
Feeding
the
poor
contribution
of
WestAfrican 1047297sheries to employment and food security Ocean Coast Manage 11172ndash81
Berkes F Folke C 1998 Linking social and ecological systems for resilience andsustainability In Berkes F Folke C (Eds) Linking Social and EcologicalSystems Management Practices and Social Mechanisms for Building ResilienceCambridge University Press Cambridge pp 1ndash25
Bernier Q Meinzen-Dick R 2014 Resilience and social capital Building Resiliencefor Food and Nutrition Security Conference Paper No 4 International FoodPolicy Research Institute Washington DC 26 p
Bhattamishra R Barrett C 2010 Community-Based risk managementarrangements a review World Dev 38 (7) 923ndash932
Boarini R Kolev A McGregor JA 2014 Measuring well-being and progress incountries at different stages of development towards a more universalconceptual framework OECD Working Paper No 235 Organisation forEconomic Co-operation and Development Development Center
ndash Better Life
Initiative Paris 59 p
Boyd E Osbahr H Ericksen P Tompkins E Carmen Lemos M Miller F 2008Resilience and
lsquoclimatizingrsquo development examples and policy implicationsDevelopment 51 390ndash396
Cam1047297eld
L
McGregor
JA
2005
Resilience
and
wellbeing
in
developing
countriesIn Ungar M (Ed) Handbook for Working with Children and Youth Pathwaysto Resilience Across Cultures and Contexts Sage Publications Thousand OaksCA
Cam1047297eld
L
Ruta
D
2007
Translation
is
not
enough
using
the
Global
PersonGenerated Index (GPGI) to assess individual quality of life in BangladeshThailand and Ethiopia Qual Life 16 (6) 1039ndash1051
Carter M Little P Mogues T Negatu W 2007 Poverty traps and natural disastersin Ethiopia and Honduras World Dev 35 (5) 835ndash856
Cleaver
F
2005
The
inequality
of
social
capital
and
the
reproduction
of
chronicpoverty World Dev 33 (6) 893ndash906
Constas M Frankenberger T Hoddinott J 2014a Resilience measurementprinciples toward an agenda for measurement design Resilience MeasurementTechnical Working Group Technical Series No 1 Food Security informationNetwork Rome
Constas MT Frankenberger J Hoddinott N Mock D Romano C Beacuteneacute DMaxwell 2014b A common analytical model for resilience measurementcausal framework and methodological options Food Security InformationNetwork (FSIN) Technical Series No 2 World Food Programme Rome
Coulthard S 2011 More than just access to 1047297sh the pros and cons of 1047297sherparticipation
in
a
customary
marine
tenure
(Padu)
system
under
pressure
MarPolicy 35 405ndash412
DFID 2011 De1047297ning Disaster Resilience A DFID Approach Paper Department forInternational Development London pp 20
Dercon S Hoddinott J Woldehanna T 2005 Shocks and consumption in 15ethiopian
villages
1999ndash2004
J
Afr
Econ
14
(4)
559ndash585Dercon S 1996 Risk crop choice and savings evidence from Tanzania Econ Dev
Cult Change 44 (3) 485ndash513Duit A Galaz V Eckerberg K 2010 Governance complexity and resilience Glob
Environ Change 20 (3) 363ndash368Eriksen
SEH
Silva
JA
2009
The
vulnerability
context
of
a
savannah
area
inMozambique household drought coping strategies and responses to economicchange Environ Sci Policy 12 (1) 33ndash52
Fafchamps M Lund S 2003 Risk-Sharing networks in rural Philippines J DevEcon 71 (2) 261ndash287
Frankenberger T Nelson S 2013 Background Paper for the Expert Consultation onResilience
Measurement
for
Food
Security
TANGO
International
Rome
Foodand Agricultural Organization and World Food Program
Heltberg R Siegel PS Jorgensen SL 2009 Addressing human vulnerability toclimate change towards a
lsquono-regretsrsquo approach Glob Environ Change 19 89ndash99
Hoddinott
J
Dercon
S
Krishnan
P
2009
Networks
and
informal
mutual
supportin 15 ethiopian villages a description In Kirsten JF Dorward AR Poulton CVink N (Eds) Institutional Economics Perspectives on African AgriculturalDevelopment International Food Policy Research Institute Washington DC pp273ndash286
Hoddinott
J
2006
Shocks
and
their
consequences
across
and
within
households
inRural Zimbabwe J Dev Stud 42 (2) 301ndash321
Intergovernmental Panel on Climate Change (IPCC) 2012 In Field CB Barros VStocker TF Qin D Dokken DJ Ebi KL Mastrandrea MD Mach KJPlattner G-K Allen SK Tignor MMidgley PM (Eds) Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation A SpecialReport of Working Groups I and II of the Intergovernmental Panel on ClimateChange Cambridge University Press Cambridge UK
Jackson T 2005 Motivating sustainable consumptionmdasha review of evidence onconsumer behaviour and behavioural change A Report to the Sustainable
Event type (Vietnam) Reduce
expenditures
Borrow
money
Reduce
Food
Change
1047297shing
strategy
Get
support
Increase
1047297shing
effort
Diversi1047297cation Seek new
collaboration
Migration Exit the
1047297shery
Sell
assets
Total
Others (aggregated) 4 7 4 6 3 0 1 3 0 0 2 30
Erosion 2 4 2 1 6 2 2 2 3 1 25
Catch reduced
suddenly
8 4 6 7 1 2 4 2 34
Gears lost 10 18 6 5 1 2 1 43
Cold wind prolongs 15 7 11 3 1 7 2 46
Typhoon
12
11
10
2
4
2
3
5
4
1
1
55
Illness
11 14
6
2
11
2
2
4
1
1
2
56Food price increase 20 17 19 2 8 5 1 72
Input price increase
continuously
47 39 33 21 40 5 6 16 1 208
Big boats compete
ground and catch
54 39 32 40 9 19 11 15 8 3 2 232
Catch
reduced
continuously
102
70
80
63
22
51
51
25
23
17
6
510
Total 285 230 209 152 105 91 87 75 39 23 15 1311
C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170 169
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
Development Research Network Centre for Environmental StrategiesUniversity of Surrey
Jones L Boyd E 2011 Exploring social barriers to adaptation insights fromWestern Nepal Glob Environ Change 21 (4) 1262ndash1274
Kallstrom HN Ljung M 2005 Social sustainability and collaborative learningAmbio 34 376ndash382
Kelty R Kelty R 2011 Human dimensions of a 1047297shery at a crossroads resourcevaluation identity and way of life in a seasonal 1047297shing community Soc NatResour
24
(4)
334ndash348Klein RJT Nicholls RJ Thomalla F 2003 Resilience to natural hazards how
useful is this concept Environ Hazards 5 35ndash45
Krosnick
JA
Fabrigar
LR
1997
Designing
rating
scales
for
effective
measurementin surveys In Lyberg L Biemer P Collins M de Leeuw E Dippo C SchwarzN
Trewin
D
(Eds)
Survey
Measurement
and
Process
Quality
John
Wiley
andSons Inc New York NY pp 141ndash164
Leichenko R OrsquoBrien K 2008 Environmental Change and Globalization DoubleExposures Oxford University Press New York
Marschke M Berkes F 2006 Exploring Strategies that build livelihood resiliencea case from Cambodia Ecol Soc 11 (1) httpwwwecologyandsocietyorgvol11iss1art42
McGregor JA Cam1047297eld L Woodcock A 2009 Needs wants and goals wellbeingquality
of
life
and
public
policy
Appl
Res
Qual
Life
4
135ndash154McGregor JA 1994 Village credit and the reproduction of poverty in rural
Bangladesh In Acheson J (Ed) Economic Anthropology and the NewInstitutional Economics University Press of AmericaSociety for EconomicAnthropology Washington pp 261ndash281 (Chapter)
McGregor
JA
2011
Reimagining
development
through
the
crisis
watch
initiative
IDS Bull 42 (5) 17ndash23McLaughlin P Dietz T 2007 Structureagency and environment toward an
integrated perspective on vulnerability Glob Environ Change 39 (4) 99ndash111Meyer MA 2013 Social capital and resilience in the context of disaster social
capital
and
collective
ef 1047297cacy
for
disaster
resilience
connecting
individualswith communities and vulnerability with resilience in hurricane-pronecommunities in Florida PhD Dissertation Department of sociology Coloradostate University Fort Collins Colorado (311 p)
Mills DJ Adhuri D Phillips M Ravikumar B Padiyar AP 2011 Shocks recoverytrajectories and resilience among aquaculture-dependent households in post-tsunami
Aceh
Indonesia
Local
Environ
Int
J
Justice
Sustain
16
(5)
425ndash444Morduch J 1995 Income smoothing and consumption smoothing J Econ
Perspect 9 (3) 103ndash114Morris S Carletto C Hoddinott J Christiaensen L 2000 J Epidemiol Commun
Health 54 381ndash387Myers
RA
Worm
B
2003
Rapid
worldwide
depletion
of
predatory 1047297sh
communities Nature 423 280ndash283Nakagawa Y Shaw R 2004 Social capital a missing link to disaster recovery Int J
Mass
Emerg
Disasters
22
(1)
5ndash
34Nussbaum MC 2001 Adaptive preferences and womenrsquos options Econ Philos 1767ndash88
Oslashstergaard N Reenberg A 2010 Cultural barriers to climate change adaptation acase study from Northern Burkina Faso Glob Environ Change 20 (1) 142ndash152
OrsquoBrien K Leichenko R 2000 Double exposure assessing the impacts of climatechange within the context of economic globalization Glob Environ Change 10221ndash232
OrsquoBrien K Eriksen S Sygna L Naess LO 2006 Questioning complacencyclimate change impacts vulnerability and adaptation in Norway AMBIO JHum Environ 35 (2) 50ndash56
OrsquoBrien K Quilan T Ziervogel G 2009 Vulnerability interventions in the contextof multiple stressors lessons from the Southern Africa vulnerability initiative(SAVI) Environ Sci Policy 12 23ndash32
OrsquoRiordan T Jordan A 1999 Institutions climate change and cultural theorytowards a common analytical framework Glob Environ Change 9 (2) 81ndash93
Pain A Levine S 2012 A conceptual analysis of livelihoods and resilienceaddressing the
lsquoinsecurity of agency HPG Working Paper OverseasDevelopment Institute Humanitarian Policy Group London
Pauly D Christensen V Dalsgaard Froese JR Torres F 1998 Fishing downmarine food webs Science 279 (5352) 860ndash863
Pelling M Manuel-Navarrete D 2011 From resilience to transformation theadaptive cycle in two Mexican urban centersEcol Soc 16 (2)11 (online) httpwwwecologyandsocietyorgvol16iss2art11
Prowse
M
Scott
L
2008
Assets
and
adaptation
an
emerging
debate
IDS
Bull
39(4) 42ndash52
Putzel J 1997 Accounting for the lsquodark sidersquo of social capital reading Robert
Putnam
on
democracy
J
Int
Dev
9
(7)
939ndash949
Quinn CH Ziervogel G Taylor A Takama T Thomalla F 2011 Coping withmultiple
stresses
in
rural
South
Africa
Ecol
Soc
16
(3)
doihttpdxdoiorg105751ES-04216-160302
Reid P Vogel C 2006 Living and responding to multiple stressors in South Africamdashglimpses from KwaZulu-Natal Glob Environ Change 16 (2) 195ndash206
Roncoli C Ingram K Kirshen P 2001 The costs and risks of coping with droughtlivelihood
impacts
and
farmersrsquo
responses
in
Burkina
Faso
Clim
Res
19
119ndash132
Schwarz AM Beacuteneacute C Bennett G Boso D Hilly Z Paul C Posala R Sibiti SAndrew N 2011 Vulnerability and resilience of rural remote communities toshocks and global changes empirical analysis from the Solomon Islands GlobEnviron Change 21 1128ndash1140
Sinha
S
Lipton
M
Yaqub
S
2002
Poverty
and
damaging 1047298uctuations
how
dothey relate J Asian Afr Stud 37 (2) 186ndash243
Tansey J OrsquoRiordan T 1999 Cultural theory and risk a review Health Risk Soc 171ndash90
Teschl M Comim F 2005 Adaptive preferences and capabilities somepreliminary
conceptual
explorations
Rev
Soc
Econ
63
(2)
229ndash247
Trimble M Johnson D 2013 Artisanal 1047297shing as an undesirable way of life Theimplications for governance of 1047297shersrsquo wellbeing aspirations in coastal Uruguayand southeastern Brazil Mar Policy 37 37ndash44
Turner BL Kasperson RE Matson P McCarthy JJ Corell RW Christensen LEckley
N
Kasperson
JX
Luers
A
Martello
ML
Polsky
C
Pulsipher
ASchiller A 2003 A framework for vulnerability analysis in sustainabilityscience Proc Natl Acad Sci 100 (14) 8074ndash8079
Vigderhous G 1977 The level of measurement and
lsquoPermissiblersquo statistical analysisin social research Pac Sociol Rev 20 (1) 61ndash72
WFP 2013 Building Resilience Through Asset Creation Resilience and PreventionUnit
Policy
Programme
and
Innovation
Division
World
Food
Program
Rome(23 p)
Walker B Carpenter S Anderies J Abel N Cumming GS Janssen M Lebel LN J Peterson GD Pritchard R 2002 Resilience management in social-ecological systems a working hypothesis for a participatory approach ConservEcol
6
(1)
14Weber EU 2010 What shapes perceptions of climate change Clim Change 1 (3)
332ndash342
Wolf
J
Adger
WN
Lorenzoni
I
Abrahamson
V
Raine
R
2010
Social
capitalindividual responses to heat waves and climate change adaptation an empiricalstudy
of
two
UK
cities
Glob
Environ
Change
20
44ndash52Wood G 2003 Staying secure staying poor the Faustian bargain World Dev 31
(3) 455ndash471World Bank 2011 Building Resilience and Opportunities World Bankrsquos Social
Protection and Labour Strategy 2012ndash2022 World Bank Washington DCYamano T Alderman H Christiaensen L 2003 Child Growth Shocks and Food
Aid in Rural Ethiopia World Bank Washington DCZimmerman F Carter M 2003 Asset smoothing consumption smoothing and the
reproduction of inequality under risk and subsistence constraints J Dev Econ71 233ndash260
von Grebmer K Headey D Beacuteneacute C Haddad L et al 2013 Global Hunger IndexThe Challenge of Hunger Building Resilience to Achieve Food and NutritionSecurity Welthungerhilfe International Food Policy Research Institute andConcern Worldwide Bonn Washington DC and Dublin
170 C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
disaster resilience National Disaster Resilience Roundtable Report 20September 2012 Melbourne Australia 36 p
Adger NW Dessai S Goulden M Hulme M Lorenzoni I Nelson DR Naess LO Wolf J Wreford A 2009 Are there social limits to adaptation to climatechange
Clim
Change
93
335ndash354Adger WN 2003 Social capital collective action and adaptation to climate
change Econ Geogr 79 (4) 387ndash404Adger WN 2006 Vulnerability Glob Environ Change 16 268ndash281Aldrich D 2010 Fixing recovery social capital in post-Crisis resilience J Homeland
Secur 6 1ndash10Ayers
J
Forsyth
T
2009
Community-based
adaptation
to
climate
changestrengthening resilience through development Environment 51 23ndash31
Beacuteneacute C Tew1047297k A 2001 Fishing effort allocation and 1047297shermenrsquos decision-makingprocess in a multi-species small-scale 1047297shery analysis of the conch and lobster1047297shery in Turks and Caicos Islands Hum Ecol 29 (2) 157ndash186
Beacuteneacute
C
Evans
L
Mills
D
Ovie
S
Raji
A
Ta1047297da
A
Kodio
A
Sinaba
F
Morand
PLemoalle J Andrew N 2011 Testing resilience thinking in a poverty contextexperience from the Niger river basin Glob Environ Change 21 (4) 1173ndash1184
Beacuteneacute C Godfrey-Wood R Newsham A Davies M2012 Resilience new utopia ornew tyranny
ndash Re1047298ection about the potentials and limits of the concept of
resilience
in
relation
to
vulnerability
reduction
programmes
IDS
Working
Paperno 405 Institute of Development Studies Brighton 61 p
Beacuteneacute C Newsham A Davies M Ulrichs M Godfrey-Wood R 2014 Resiliencepoverty and development J Int Dev 26 598ndash623
Beacuteneacute C Waid J Jackson-deGraffenried M Begum A Chowdhury M Skarin VRahman A Islam N Mamnun N Mainuddin K Shah MA 2015a Impact of climate-related
shocks
and
stresses
on
nutrition
and
food
security
in
ruralBangladesh Dhaka World Food Programme 119 p
Beacuteneacute C Frankenberger T Nelson S 2015b Design monitoring and evaluation of resilience interventions conceptual and empirical considerations IDS WorkingPaper no459 Institute of Development Studies 23 p
Beacuteneacute
C
2013
Towards
a
quanti1047297able
measure
of
resilience
IDS
Working
Paper
434Institute of Development Studies Brighton 27 p
Bandura A 1977 Self-ef 1047297cacy toward a unifying theory of behavioral changePsychol Rev 84 191ndash215
Baulch R Hoddinott J 2000 Economic mobility and poverty dynamics indeveloping countries J Dev Stud 36 (6) 1ndash23
Belhabib
D
Sumaila
UR
Pauly
D
2015
Feeding
the
poor
contribution
of
WestAfrican 1047297sheries to employment and food security Ocean Coast Manage 11172ndash81
Berkes F Folke C 1998 Linking social and ecological systems for resilience andsustainability In Berkes F Folke C (Eds) Linking Social and EcologicalSystems Management Practices and Social Mechanisms for Building ResilienceCambridge University Press Cambridge pp 1ndash25
Bernier Q Meinzen-Dick R 2014 Resilience and social capital Building Resiliencefor Food and Nutrition Security Conference Paper No 4 International FoodPolicy Research Institute Washington DC 26 p
Bhattamishra R Barrett C 2010 Community-Based risk managementarrangements a review World Dev 38 (7) 923ndash932
Boarini R Kolev A McGregor JA 2014 Measuring well-being and progress incountries at different stages of development towards a more universalconceptual framework OECD Working Paper No 235 Organisation forEconomic Co-operation and Development Development Center
ndash Better Life
Initiative Paris 59 p
Boyd E Osbahr H Ericksen P Tompkins E Carmen Lemos M Miller F 2008Resilience and
lsquoclimatizingrsquo development examples and policy implicationsDevelopment 51 390ndash396
Cam1047297eld
L
McGregor
JA
2005
Resilience
and
wellbeing
in
developing
countriesIn Ungar M (Ed) Handbook for Working with Children and Youth Pathwaysto Resilience Across Cultures and Contexts Sage Publications Thousand OaksCA
Cam1047297eld
L
Ruta
D
2007
Translation
is
not
enough
using
the
Global
PersonGenerated Index (GPGI) to assess individual quality of life in BangladeshThailand and Ethiopia Qual Life 16 (6) 1039ndash1051
Carter M Little P Mogues T Negatu W 2007 Poverty traps and natural disastersin Ethiopia and Honduras World Dev 35 (5) 835ndash856
Cleaver
F
2005
The
inequality
of
social
capital
and
the
reproduction
of
chronicpoverty World Dev 33 (6) 893ndash906
Constas M Frankenberger T Hoddinott J 2014a Resilience measurementprinciples toward an agenda for measurement design Resilience MeasurementTechnical Working Group Technical Series No 1 Food Security informationNetwork Rome
Constas MT Frankenberger J Hoddinott N Mock D Romano C Beacuteneacute DMaxwell 2014b A common analytical model for resilience measurementcausal framework and methodological options Food Security InformationNetwork (FSIN) Technical Series No 2 World Food Programme Rome
Coulthard S 2011 More than just access to 1047297sh the pros and cons of 1047297sherparticipation
in
a
customary
marine
tenure
(Padu)
system
under
pressure
MarPolicy 35 405ndash412
DFID 2011 De1047297ning Disaster Resilience A DFID Approach Paper Department forInternational Development London pp 20
Dercon S Hoddinott J Woldehanna T 2005 Shocks and consumption in 15ethiopian
villages
1999ndash2004
J
Afr
Econ
14
(4)
559ndash585Dercon S 1996 Risk crop choice and savings evidence from Tanzania Econ Dev
Cult Change 44 (3) 485ndash513Duit A Galaz V Eckerberg K 2010 Governance complexity and resilience Glob
Environ Change 20 (3) 363ndash368Eriksen
SEH
Silva
JA
2009
The
vulnerability
context
of
a
savannah
area
inMozambique household drought coping strategies and responses to economicchange Environ Sci Policy 12 (1) 33ndash52
Fafchamps M Lund S 2003 Risk-Sharing networks in rural Philippines J DevEcon 71 (2) 261ndash287
Frankenberger T Nelson S 2013 Background Paper for the Expert Consultation onResilience
Measurement
for
Food
Security
TANGO
International
Rome
Foodand Agricultural Organization and World Food Program
Heltberg R Siegel PS Jorgensen SL 2009 Addressing human vulnerability toclimate change towards a
lsquono-regretsrsquo approach Glob Environ Change 19 89ndash99
Hoddinott
J
Dercon
S
Krishnan
P
2009
Networks
and
informal
mutual
supportin 15 ethiopian villages a description In Kirsten JF Dorward AR Poulton CVink N (Eds) Institutional Economics Perspectives on African AgriculturalDevelopment International Food Policy Research Institute Washington DC pp273ndash286
Hoddinott
J
2006
Shocks
and
their
consequences
across
and
within
households
inRural Zimbabwe J Dev Stud 42 (2) 301ndash321
Intergovernmental Panel on Climate Change (IPCC) 2012 In Field CB Barros VStocker TF Qin D Dokken DJ Ebi KL Mastrandrea MD Mach KJPlattner G-K Allen SK Tignor MMidgley PM (Eds) Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation A SpecialReport of Working Groups I and II of the Intergovernmental Panel on ClimateChange Cambridge University Press Cambridge UK
Jackson T 2005 Motivating sustainable consumptionmdasha review of evidence onconsumer behaviour and behavioural change A Report to the Sustainable
Event type (Vietnam) Reduce
expenditures
Borrow
money
Reduce
Food
Change
1047297shing
strategy
Get
support
Increase
1047297shing
effort
Diversi1047297cation Seek new
collaboration
Migration Exit the
1047297shery
Sell
assets
Total
Others (aggregated) 4 7 4 6 3 0 1 3 0 0 2 30
Erosion 2 4 2 1 6 2 2 2 3 1 25
Catch reduced
suddenly
8 4 6 7 1 2 4 2 34
Gears lost 10 18 6 5 1 2 1 43
Cold wind prolongs 15 7 11 3 1 7 2 46
Typhoon
12
11
10
2
4
2
3
5
4
1
1
55
Illness
11 14
6
2
11
2
2
4
1
1
2
56Food price increase 20 17 19 2 8 5 1 72
Input price increase
continuously
47 39 33 21 40 5 6 16 1 208
Big boats compete
ground and catch
54 39 32 40 9 19 11 15 8 3 2 232
Catch
reduced
continuously
102
70
80
63
22
51
51
25
23
17
6
510
Total 285 230 209 152 105 91 87 75 39 23 15 1311
C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170 169
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
Development Research Network Centre for Environmental StrategiesUniversity of Surrey
Jones L Boyd E 2011 Exploring social barriers to adaptation insights fromWestern Nepal Glob Environ Change 21 (4) 1262ndash1274
Kallstrom HN Ljung M 2005 Social sustainability and collaborative learningAmbio 34 376ndash382
Kelty R Kelty R 2011 Human dimensions of a 1047297shery at a crossroads resourcevaluation identity and way of life in a seasonal 1047297shing community Soc NatResour
24
(4)
334ndash348Klein RJT Nicholls RJ Thomalla F 2003 Resilience to natural hazards how
useful is this concept Environ Hazards 5 35ndash45
Krosnick
JA
Fabrigar
LR
1997
Designing
rating
scales
for
effective
measurementin surveys In Lyberg L Biemer P Collins M de Leeuw E Dippo C SchwarzN
Trewin
D
(Eds)
Survey
Measurement
and
Process
Quality
John
Wiley
andSons Inc New York NY pp 141ndash164
Leichenko R OrsquoBrien K 2008 Environmental Change and Globalization DoubleExposures Oxford University Press New York
Marschke M Berkes F 2006 Exploring Strategies that build livelihood resiliencea case from Cambodia Ecol Soc 11 (1) httpwwwecologyandsocietyorgvol11iss1art42
McGregor JA Cam1047297eld L Woodcock A 2009 Needs wants and goals wellbeingquality
of
life
and
public
policy
Appl
Res
Qual
Life
4
135ndash154McGregor JA 1994 Village credit and the reproduction of poverty in rural
Bangladesh In Acheson J (Ed) Economic Anthropology and the NewInstitutional Economics University Press of AmericaSociety for EconomicAnthropology Washington pp 261ndash281 (Chapter)
McGregor
JA
2011
Reimagining
development
through
the
crisis
watch
initiative
IDS Bull 42 (5) 17ndash23McLaughlin P Dietz T 2007 Structureagency and environment toward an
integrated perspective on vulnerability Glob Environ Change 39 (4) 99ndash111Meyer MA 2013 Social capital and resilience in the context of disaster social
capital
and
collective
ef 1047297cacy
for
disaster
resilience
connecting
individualswith communities and vulnerability with resilience in hurricane-pronecommunities in Florida PhD Dissertation Department of sociology Coloradostate University Fort Collins Colorado (311 p)
Mills DJ Adhuri D Phillips M Ravikumar B Padiyar AP 2011 Shocks recoverytrajectories and resilience among aquaculture-dependent households in post-tsunami
Aceh
Indonesia
Local
Environ
Int
J
Justice
Sustain
16
(5)
425ndash444Morduch J 1995 Income smoothing and consumption smoothing J Econ
Perspect 9 (3) 103ndash114Morris S Carletto C Hoddinott J Christiaensen L 2000 J Epidemiol Commun
Health 54 381ndash387Myers
RA
Worm
B
2003
Rapid
worldwide
depletion
of
predatory 1047297sh
communities Nature 423 280ndash283Nakagawa Y Shaw R 2004 Social capital a missing link to disaster recovery Int J
Mass
Emerg
Disasters
22
(1)
5ndash
34Nussbaum MC 2001 Adaptive preferences and womenrsquos options Econ Philos 1767ndash88
Oslashstergaard N Reenberg A 2010 Cultural barriers to climate change adaptation acase study from Northern Burkina Faso Glob Environ Change 20 (1) 142ndash152
OrsquoBrien K Leichenko R 2000 Double exposure assessing the impacts of climatechange within the context of economic globalization Glob Environ Change 10221ndash232
OrsquoBrien K Eriksen S Sygna L Naess LO 2006 Questioning complacencyclimate change impacts vulnerability and adaptation in Norway AMBIO JHum Environ 35 (2) 50ndash56
OrsquoBrien K Quilan T Ziervogel G 2009 Vulnerability interventions in the contextof multiple stressors lessons from the Southern Africa vulnerability initiative(SAVI) Environ Sci Policy 12 23ndash32
OrsquoRiordan T Jordan A 1999 Institutions climate change and cultural theorytowards a common analytical framework Glob Environ Change 9 (2) 81ndash93
Pain A Levine S 2012 A conceptual analysis of livelihoods and resilienceaddressing the
lsquoinsecurity of agency HPG Working Paper OverseasDevelopment Institute Humanitarian Policy Group London
Pauly D Christensen V Dalsgaard Froese JR Torres F 1998 Fishing downmarine food webs Science 279 (5352) 860ndash863
Pelling M Manuel-Navarrete D 2011 From resilience to transformation theadaptive cycle in two Mexican urban centersEcol Soc 16 (2)11 (online) httpwwwecologyandsocietyorgvol16iss2art11
Prowse
M
Scott
L
2008
Assets
and
adaptation
an
emerging
debate
IDS
Bull
39(4) 42ndash52
Putzel J 1997 Accounting for the lsquodark sidersquo of social capital reading Robert
Putnam
on
democracy
J
Int
Dev
9
(7)
939ndash949
Quinn CH Ziervogel G Taylor A Takama T Thomalla F 2011 Coping withmultiple
stresses
in
rural
South
Africa
Ecol
Soc
16
(3)
doihttpdxdoiorg105751ES-04216-160302
Reid P Vogel C 2006 Living and responding to multiple stressors in South Africamdashglimpses from KwaZulu-Natal Glob Environ Change 16 (2) 195ndash206
Roncoli C Ingram K Kirshen P 2001 The costs and risks of coping with droughtlivelihood
impacts
and
farmersrsquo
responses
in
Burkina
Faso
Clim
Res
19
119ndash132
Schwarz AM Beacuteneacute C Bennett G Boso D Hilly Z Paul C Posala R Sibiti SAndrew N 2011 Vulnerability and resilience of rural remote communities toshocks and global changes empirical analysis from the Solomon Islands GlobEnviron Change 21 1128ndash1140
Sinha
S
Lipton
M
Yaqub
S
2002
Poverty
and
damaging 1047298uctuations
how
dothey relate J Asian Afr Stud 37 (2) 186ndash243
Tansey J OrsquoRiordan T 1999 Cultural theory and risk a review Health Risk Soc 171ndash90
Teschl M Comim F 2005 Adaptive preferences and capabilities somepreliminary
conceptual
explorations
Rev
Soc
Econ
63
(2)
229ndash247
Trimble M Johnson D 2013 Artisanal 1047297shing as an undesirable way of life Theimplications for governance of 1047297shersrsquo wellbeing aspirations in coastal Uruguayand southeastern Brazil Mar Policy 37 37ndash44
Turner BL Kasperson RE Matson P McCarthy JJ Corell RW Christensen LEckley
N
Kasperson
JX
Luers
A
Martello
ML
Polsky
C
Pulsipher
ASchiller A 2003 A framework for vulnerability analysis in sustainabilityscience Proc Natl Acad Sci 100 (14) 8074ndash8079
Vigderhous G 1977 The level of measurement and
lsquoPermissiblersquo statistical analysisin social research Pac Sociol Rev 20 (1) 61ndash72
WFP 2013 Building Resilience Through Asset Creation Resilience and PreventionUnit
Policy
Programme
and
Innovation
Division
World
Food
Program
Rome(23 p)
Walker B Carpenter S Anderies J Abel N Cumming GS Janssen M Lebel LN J Peterson GD Pritchard R 2002 Resilience management in social-ecological systems a working hypothesis for a participatory approach ConservEcol
6
(1)
14Weber EU 2010 What shapes perceptions of climate change Clim Change 1 (3)
332ndash342
Wolf
J
Adger
WN
Lorenzoni
I
Abrahamson
V
Raine
R
2010
Social
capitalindividual responses to heat waves and climate change adaptation an empiricalstudy
of
two
UK
cities
Glob
Environ
Change
20
44ndash52Wood G 2003 Staying secure staying poor the Faustian bargain World Dev 31
(3) 455ndash471World Bank 2011 Building Resilience and Opportunities World Bankrsquos Social
Protection and Labour Strategy 2012ndash2022 World Bank Washington DCYamano T Alderman H Christiaensen L 2003 Child Growth Shocks and Food
Aid in Rural Ethiopia World Bank Washington DCZimmerman F Carter M 2003 Asset smoothing consumption smoothing and the
reproduction of inequality under risk and subsistence constraints J Dev Econ71 233ndash260
von Grebmer K Headey D Beacuteneacute C Haddad L et al 2013 Global Hunger IndexThe Challenge of Hunger Building Resilience to Achieve Food and NutritionSecurity Welthungerhilfe International Food Policy Research Institute andConcern Worldwide Bonn Washington DC and Dublin
170 C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
disaster resilience National Disaster Resilience Roundtable Report 20September 2012 Melbourne Australia 36 p
Adger NW Dessai S Goulden M Hulme M Lorenzoni I Nelson DR Naess LO Wolf J Wreford A 2009 Are there social limits to adaptation to climatechange
Clim
Change
93
335ndash354Adger WN 2003 Social capital collective action and adaptation to climate
change Econ Geogr 79 (4) 387ndash404Adger WN 2006 Vulnerability Glob Environ Change 16 268ndash281Aldrich D 2010 Fixing recovery social capital in post-Crisis resilience J Homeland
Secur 6 1ndash10Ayers
J
Forsyth
T
2009
Community-based
adaptation
to
climate
changestrengthening resilience through development Environment 51 23ndash31
Beacuteneacute C Tew1047297k A 2001 Fishing effort allocation and 1047297shermenrsquos decision-makingprocess in a multi-species small-scale 1047297shery analysis of the conch and lobster1047297shery in Turks and Caicos Islands Hum Ecol 29 (2) 157ndash186
Beacuteneacute
C
Evans
L
Mills
D
Ovie
S
Raji
A
Ta1047297da
A
Kodio
A
Sinaba
F
Morand
PLemoalle J Andrew N 2011 Testing resilience thinking in a poverty contextexperience from the Niger river basin Glob Environ Change 21 (4) 1173ndash1184
Beacuteneacute C Godfrey-Wood R Newsham A Davies M2012 Resilience new utopia ornew tyranny
ndash Re1047298ection about the potentials and limits of the concept of
resilience
in
relation
to
vulnerability
reduction
programmes
IDS
Working
Paperno 405 Institute of Development Studies Brighton 61 p
Beacuteneacute C Newsham A Davies M Ulrichs M Godfrey-Wood R 2014 Resiliencepoverty and development J Int Dev 26 598ndash623
Beacuteneacute C Waid J Jackson-deGraffenried M Begum A Chowdhury M Skarin VRahman A Islam N Mamnun N Mainuddin K Shah MA 2015a Impact of climate-related
shocks
and
stresses
on
nutrition
and
food
security
in
ruralBangladesh Dhaka World Food Programme 119 p
Beacuteneacute C Frankenberger T Nelson S 2015b Design monitoring and evaluation of resilience interventions conceptual and empirical considerations IDS WorkingPaper no459 Institute of Development Studies 23 p
Beacuteneacute
C
2013
Towards
a
quanti1047297able
measure
of
resilience
IDS
Working
Paper
434Institute of Development Studies Brighton 27 p
Bandura A 1977 Self-ef 1047297cacy toward a unifying theory of behavioral changePsychol Rev 84 191ndash215
Baulch R Hoddinott J 2000 Economic mobility and poverty dynamics indeveloping countries J Dev Stud 36 (6) 1ndash23
Belhabib
D
Sumaila
UR
Pauly
D
2015
Feeding
the
poor
contribution
of
WestAfrican 1047297sheries to employment and food security Ocean Coast Manage 11172ndash81
Berkes F Folke C 1998 Linking social and ecological systems for resilience andsustainability In Berkes F Folke C (Eds) Linking Social and EcologicalSystems Management Practices and Social Mechanisms for Building ResilienceCambridge University Press Cambridge pp 1ndash25
Bernier Q Meinzen-Dick R 2014 Resilience and social capital Building Resiliencefor Food and Nutrition Security Conference Paper No 4 International FoodPolicy Research Institute Washington DC 26 p
Bhattamishra R Barrett C 2010 Community-Based risk managementarrangements a review World Dev 38 (7) 923ndash932
Boarini R Kolev A McGregor JA 2014 Measuring well-being and progress incountries at different stages of development towards a more universalconceptual framework OECD Working Paper No 235 Organisation forEconomic Co-operation and Development Development Center
ndash Better Life
Initiative Paris 59 p
Boyd E Osbahr H Ericksen P Tompkins E Carmen Lemos M Miller F 2008Resilience and
lsquoclimatizingrsquo development examples and policy implicationsDevelopment 51 390ndash396
Cam1047297eld
L
McGregor
JA
2005
Resilience
and
wellbeing
in
developing
countriesIn Ungar M (Ed) Handbook for Working with Children and Youth Pathwaysto Resilience Across Cultures and Contexts Sage Publications Thousand OaksCA
Cam1047297eld
L
Ruta
D
2007
Translation
is
not
enough
using
the
Global
PersonGenerated Index (GPGI) to assess individual quality of life in BangladeshThailand and Ethiopia Qual Life 16 (6) 1039ndash1051
Carter M Little P Mogues T Negatu W 2007 Poverty traps and natural disastersin Ethiopia and Honduras World Dev 35 (5) 835ndash856
Cleaver
F
2005
The
inequality
of
social
capital
and
the
reproduction
of
chronicpoverty World Dev 33 (6) 893ndash906
Constas M Frankenberger T Hoddinott J 2014a Resilience measurementprinciples toward an agenda for measurement design Resilience MeasurementTechnical Working Group Technical Series No 1 Food Security informationNetwork Rome
Constas MT Frankenberger J Hoddinott N Mock D Romano C Beacuteneacute DMaxwell 2014b A common analytical model for resilience measurementcausal framework and methodological options Food Security InformationNetwork (FSIN) Technical Series No 2 World Food Programme Rome
Coulthard S 2011 More than just access to 1047297sh the pros and cons of 1047297sherparticipation
in
a
customary
marine
tenure
(Padu)
system
under
pressure
MarPolicy 35 405ndash412
DFID 2011 De1047297ning Disaster Resilience A DFID Approach Paper Department forInternational Development London pp 20
Dercon S Hoddinott J Woldehanna T 2005 Shocks and consumption in 15ethiopian
villages
1999ndash2004
J
Afr
Econ
14
(4)
559ndash585Dercon S 1996 Risk crop choice and savings evidence from Tanzania Econ Dev
Cult Change 44 (3) 485ndash513Duit A Galaz V Eckerberg K 2010 Governance complexity and resilience Glob
Environ Change 20 (3) 363ndash368Eriksen
SEH
Silva
JA
2009
The
vulnerability
context
of
a
savannah
area
inMozambique household drought coping strategies and responses to economicchange Environ Sci Policy 12 (1) 33ndash52
Fafchamps M Lund S 2003 Risk-Sharing networks in rural Philippines J DevEcon 71 (2) 261ndash287
Frankenberger T Nelson S 2013 Background Paper for the Expert Consultation onResilience
Measurement
for
Food
Security
TANGO
International
Rome
Foodand Agricultural Organization and World Food Program
Heltberg R Siegel PS Jorgensen SL 2009 Addressing human vulnerability toclimate change towards a
lsquono-regretsrsquo approach Glob Environ Change 19 89ndash99
Hoddinott
J
Dercon
S
Krishnan
P
2009
Networks
and
informal
mutual
supportin 15 ethiopian villages a description In Kirsten JF Dorward AR Poulton CVink N (Eds) Institutional Economics Perspectives on African AgriculturalDevelopment International Food Policy Research Institute Washington DC pp273ndash286
Hoddinott
J
2006
Shocks
and
their
consequences
across
and
within
households
inRural Zimbabwe J Dev Stud 42 (2) 301ndash321
Intergovernmental Panel on Climate Change (IPCC) 2012 In Field CB Barros VStocker TF Qin D Dokken DJ Ebi KL Mastrandrea MD Mach KJPlattner G-K Allen SK Tignor MMidgley PM (Eds) Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation A SpecialReport of Working Groups I and II of the Intergovernmental Panel on ClimateChange Cambridge University Press Cambridge UK
Jackson T 2005 Motivating sustainable consumptionmdasha review of evidence onconsumer behaviour and behavioural change A Report to the Sustainable
Event type (Vietnam) Reduce
expenditures
Borrow
money
Reduce
Food
Change
1047297shing
strategy
Get
support
Increase
1047297shing
effort
Diversi1047297cation Seek new
collaboration
Migration Exit the
1047297shery
Sell
assets
Total
Others (aggregated) 4 7 4 6 3 0 1 3 0 0 2 30
Erosion 2 4 2 1 6 2 2 2 3 1 25
Catch reduced
suddenly
8 4 6 7 1 2 4 2 34
Gears lost 10 18 6 5 1 2 1 43
Cold wind prolongs 15 7 11 3 1 7 2 46
Typhoon
12
11
10
2
4
2
3
5
4
1
1
55
Illness
11 14
6
2
11
2
2
4
1
1
2
56Food price increase 20 17 19 2 8 5 1 72
Input price increase
continuously
47 39 33 21 40 5 6 16 1 208
Big boats compete
ground and catch
54 39 32 40 9 19 11 15 8 3 2 232
Catch
reduced
continuously
102
70
80
63
22
51
51
25
23
17
6
510
Total 285 230 209 152 105 91 87 75 39 23 15 1311
C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170 169
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
Development Research Network Centre for Environmental StrategiesUniversity of Surrey
Jones L Boyd E 2011 Exploring social barriers to adaptation insights fromWestern Nepal Glob Environ Change 21 (4) 1262ndash1274
Kallstrom HN Ljung M 2005 Social sustainability and collaborative learningAmbio 34 376ndash382
Kelty R Kelty R 2011 Human dimensions of a 1047297shery at a crossroads resourcevaluation identity and way of life in a seasonal 1047297shing community Soc NatResour
24
(4)
334ndash348Klein RJT Nicholls RJ Thomalla F 2003 Resilience to natural hazards how
useful is this concept Environ Hazards 5 35ndash45
Krosnick
JA
Fabrigar
LR
1997
Designing
rating
scales
for
effective
measurementin surveys In Lyberg L Biemer P Collins M de Leeuw E Dippo C SchwarzN
Trewin
D
(Eds)
Survey
Measurement
and
Process
Quality
John
Wiley
andSons Inc New York NY pp 141ndash164
Leichenko R OrsquoBrien K 2008 Environmental Change and Globalization DoubleExposures Oxford University Press New York
Marschke M Berkes F 2006 Exploring Strategies that build livelihood resiliencea case from Cambodia Ecol Soc 11 (1) httpwwwecologyandsocietyorgvol11iss1art42
McGregor JA Cam1047297eld L Woodcock A 2009 Needs wants and goals wellbeingquality
of
life
and
public
policy
Appl
Res
Qual
Life
4
135ndash154McGregor JA 1994 Village credit and the reproduction of poverty in rural
Bangladesh In Acheson J (Ed) Economic Anthropology and the NewInstitutional Economics University Press of AmericaSociety for EconomicAnthropology Washington pp 261ndash281 (Chapter)
McGregor
JA
2011
Reimagining
development
through
the
crisis
watch
initiative
IDS Bull 42 (5) 17ndash23McLaughlin P Dietz T 2007 Structureagency and environment toward an
integrated perspective on vulnerability Glob Environ Change 39 (4) 99ndash111Meyer MA 2013 Social capital and resilience in the context of disaster social
capital
and
collective
ef 1047297cacy
for
disaster
resilience
connecting
individualswith communities and vulnerability with resilience in hurricane-pronecommunities in Florida PhD Dissertation Department of sociology Coloradostate University Fort Collins Colorado (311 p)
Mills DJ Adhuri D Phillips M Ravikumar B Padiyar AP 2011 Shocks recoverytrajectories and resilience among aquaculture-dependent households in post-tsunami
Aceh
Indonesia
Local
Environ
Int
J
Justice
Sustain
16
(5)
425ndash444Morduch J 1995 Income smoothing and consumption smoothing J Econ
Perspect 9 (3) 103ndash114Morris S Carletto C Hoddinott J Christiaensen L 2000 J Epidemiol Commun
Health 54 381ndash387Myers
RA
Worm
B
2003
Rapid
worldwide
depletion
of
predatory 1047297sh
communities Nature 423 280ndash283Nakagawa Y Shaw R 2004 Social capital a missing link to disaster recovery Int J
Mass
Emerg
Disasters
22
(1)
5ndash
34Nussbaum MC 2001 Adaptive preferences and womenrsquos options Econ Philos 1767ndash88
Oslashstergaard N Reenberg A 2010 Cultural barriers to climate change adaptation acase study from Northern Burkina Faso Glob Environ Change 20 (1) 142ndash152
OrsquoBrien K Leichenko R 2000 Double exposure assessing the impacts of climatechange within the context of economic globalization Glob Environ Change 10221ndash232
OrsquoBrien K Eriksen S Sygna L Naess LO 2006 Questioning complacencyclimate change impacts vulnerability and adaptation in Norway AMBIO JHum Environ 35 (2) 50ndash56
OrsquoBrien K Quilan T Ziervogel G 2009 Vulnerability interventions in the contextof multiple stressors lessons from the Southern Africa vulnerability initiative(SAVI) Environ Sci Policy 12 23ndash32
OrsquoRiordan T Jordan A 1999 Institutions climate change and cultural theorytowards a common analytical framework Glob Environ Change 9 (2) 81ndash93
Pain A Levine S 2012 A conceptual analysis of livelihoods and resilienceaddressing the
lsquoinsecurity of agency HPG Working Paper OverseasDevelopment Institute Humanitarian Policy Group London
Pauly D Christensen V Dalsgaard Froese JR Torres F 1998 Fishing downmarine food webs Science 279 (5352) 860ndash863
Pelling M Manuel-Navarrete D 2011 From resilience to transformation theadaptive cycle in two Mexican urban centersEcol Soc 16 (2)11 (online) httpwwwecologyandsocietyorgvol16iss2art11
Prowse
M
Scott
L
2008
Assets
and
adaptation
an
emerging
debate
IDS
Bull
39(4) 42ndash52
Putzel J 1997 Accounting for the lsquodark sidersquo of social capital reading Robert
Putnam
on
democracy
J
Int
Dev
9
(7)
939ndash949
Quinn CH Ziervogel G Taylor A Takama T Thomalla F 2011 Coping withmultiple
stresses
in
rural
South
Africa
Ecol
Soc
16
(3)
doihttpdxdoiorg105751ES-04216-160302
Reid P Vogel C 2006 Living and responding to multiple stressors in South Africamdashglimpses from KwaZulu-Natal Glob Environ Change 16 (2) 195ndash206
Roncoli C Ingram K Kirshen P 2001 The costs and risks of coping with droughtlivelihood
impacts
and
farmersrsquo
responses
in
Burkina
Faso
Clim
Res
19
119ndash132
Schwarz AM Beacuteneacute C Bennett G Boso D Hilly Z Paul C Posala R Sibiti SAndrew N 2011 Vulnerability and resilience of rural remote communities toshocks and global changes empirical analysis from the Solomon Islands GlobEnviron Change 21 1128ndash1140
Sinha
S
Lipton
M
Yaqub
S
2002
Poverty
and
damaging 1047298uctuations
how
dothey relate J Asian Afr Stud 37 (2) 186ndash243
Tansey J OrsquoRiordan T 1999 Cultural theory and risk a review Health Risk Soc 171ndash90
Teschl M Comim F 2005 Adaptive preferences and capabilities somepreliminary
conceptual
explorations
Rev
Soc
Econ
63
(2)
229ndash247
Trimble M Johnson D 2013 Artisanal 1047297shing as an undesirable way of life Theimplications for governance of 1047297shersrsquo wellbeing aspirations in coastal Uruguayand southeastern Brazil Mar Policy 37 37ndash44
Turner BL Kasperson RE Matson P McCarthy JJ Corell RW Christensen LEckley
N
Kasperson
JX
Luers
A
Martello
ML
Polsky
C
Pulsipher
ASchiller A 2003 A framework for vulnerability analysis in sustainabilityscience Proc Natl Acad Sci 100 (14) 8074ndash8079
Vigderhous G 1977 The level of measurement and
lsquoPermissiblersquo statistical analysisin social research Pac Sociol Rev 20 (1) 61ndash72
WFP 2013 Building Resilience Through Asset Creation Resilience and PreventionUnit
Policy
Programme
and
Innovation
Division
World
Food
Program
Rome(23 p)
Walker B Carpenter S Anderies J Abel N Cumming GS Janssen M Lebel LN J Peterson GD Pritchard R 2002 Resilience management in social-ecological systems a working hypothesis for a participatory approach ConservEcol
6
(1)
14Weber EU 2010 What shapes perceptions of climate change Clim Change 1 (3)
332ndash342
Wolf
J
Adger
WN
Lorenzoni
I
Abrahamson
V
Raine
R
2010
Social
capitalindividual responses to heat waves and climate change adaptation an empiricalstudy
of
two
UK
cities
Glob
Environ
Change
20
44ndash52Wood G 2003 Staying secure staying poor the Faustian bargain World Dev 31
(3) 455ndash471World Bank 2011 Building Resilience and Opportunities World Bankrsquos Social
Protection and Labour Strategy 2012ndash2022 World Bank Washington DCYamano T Alderman H Christiaensen L 2003 Child Growth Shocks and Food
Aid in Rural Ethiopia World Bank Washington DCZimmerman F Carter M 2003 Asset smoothing consumption smoothing and the
reproduction of inequality under risk and subsistence constraints J Dev Econ71 233ndash260
von Grebmer K Headey D Beacuteneacute C Haddad L et al 2013 Global Hunger IndexThe Challenge of Hunger Building Resilience to Achieve Food and NutritionSecurity Welthungerhilfe International Food Policy Research Institute andConcern Worldwide Bonn Washington DC and Dublin
170 C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
disaster resilience National Disaster Resilience Roundtable Report 20September 2012 Melbourne Australia 36 p
Adger NW Dessai S Goulden M Hulme M Lorenzoni I Nelson DR Naess LO Wolf J Wreford A 2009 Are there social limits to adaptation to climatechange
Clim
Change
93
335ndash354Adger WN 2003 Social capital collective action and adaptation to climate
change Econ Geogr 79 (4) 387ndash404Adger WN 2006 Vulnerability Glob Environ Change 16 268ndash281Aldrich D 2010 Fixing recovery social capital in post-Crisis resilience J Homeland
Secur 6 1ndash10Ayers
J
Forsyth
T
2009
Community-based
adaptation
to
climate
changestrengthening resilience through development Environment 51 23ndash31
Beacuteneacute C Tew1047297k A 2001 Fishing effort allocation and 1047297shermenrsquos decision-makingprocess in a multi-species small-scale 1047297shery analysis of the conch and lobster1047297shery in Turks and Caicos Islands Hum Ecol 29 (2) 157ndash186
Beacuteneacute
C
Evans
L
Mills
D
Ovie
S
Raji
A
Ta1047297da
A
Kodio
A
Sinaba
F
Morand
PLemoalle J Andrew N 2011 Testing resilience thinking in a poverty contextexperience from the Niger river basin Glob Environ Change 21 (4) 1173ndash1184
Beacuteneacute C Godfrey-Wood R Newsham A Davies M2012 Resilience new utopia ornew tyranny
ndash Re1047298ection about the potentials and limits of the concept of
resilience
in
relation
to
vulnerability
reduction
programmes
IDS
Working
Paperno 405 Institute of Development Studies Brighton 61 p
Beacuteneacute C Newsham A Davies M Ulrichs M Godfrey-Wood R 2014 Resiliencepoverty and development J Int Dev 26 598ndash623
Beacuteneacute C Waid J Jackson-deGraffenried M Begum A Chowdhury M Skarin VRahman A Islam N Mamnun N Mainuddin K Shah MA 2015a Impact of climate-related
shocks
and
stresses
on
nutrition
and
food
security
in
ruralBangladesh Dhaka World Food Programme 119 p
Beacuteneacute C Frankenberger T Nelson S 2015b Design monitoring and evaluation of resilience interventions conceptual and empirical considerations IDS WorkingPaper no459 Institute of Development Studies 23 p
Beacuteneacute
C
2013
Towards
a
quanti1047297able
measure
of
resilience
IDS
Working
Paper
434Institute of Development Studies Brighton 27 p
Bandura A 1977 Self-ef 1047297cacy toward a unifying theory of behavioral changePsychol Rev 84 191ndash215
Baulch R Hoddinott J 2000 Economic mobility and poverty dynamics indeveloping countries J Dev Stud 36 (6) 1ndash23
Belhabib
D
Sumaila
UR
Pauly
D
2015
Feeding
the
poor
contribution
of
WestAfrican 1047297sheries to employment and food security Ocean Coast Manage 11172ndash81
Berkes F Folke C 1998 Linking social and ecological systems for resilience andsustainability In Berkes F Folke C (Eds) Linking Social and EcologicalSystems Management Practices and Social Mechanisms for Building ResilienceCambridge University Press Cambridge pp 1ndash25
Bernier Q Meinzen-Dick R 2014 Resilience and social capital Building Resiliencefor Food and Nutrition Security Conference Paper No 4 International FoodPolicy Research Institute Washington DC 26 p
Bhattamishra R Barrett C 2010 Community-Based risk managementarrangements a review World Dev 38 (7) 923ndash932
Boarini R Kolev A McGregor JA 2014 Measuring well-being and progress incountries at different stages of development towards a more universalconceptual framework OECD Working Paper No 235 Organisation forEconomic Co-operation and Development Development Center
ndash Better Life
Initiative Paris 59 p
Boyd E Osbahr H Ericksen P Tompkins E Carmen Lemos M Miller F 2008Resilience and
lsquoclimatizingrsquo development examples and policy implicationsDevelopment 51 390ndash396
Cam1047297eld
L
McGregor
JA
2005
Resilience
and
wellbeing
in
developing
countriesIn Ungar M (Ed) Handbook for Working with Children and Youth Pathwaysto Resilience Across Cultures and Contexts Sage Publications Thousand OaksCA
Cam1047297eld
L
Ruta
D
2007
Translation
is
not
enough
using
the
Global
PersonGenerated Index (GPGI) to assess individual quality of life in BangladeshThailand and Ethiopia Qual Life 16 (6) 1039ndash1051
Carter M Little P Mogues T Negatu W 2007 Poverty traps and natural disastersin Ethiopia and Honduras World Dev 35 (5) 835ndash856
Cleaver
F
2005
The
inequality
of
social
capital
and
the
reproduction
of
chronicpoverty World Dev 33 (6) 893ndash906
Constas M Frankenberger T Hoddinott J 2014a Resilience measurementprinciples toward an agenda for measurement design Resilience MeasurementTechnical Working Group Technical Series No 1 Food Security informationNetwork Rome
Constas MT Frankenberger J Hoddinott N Mock D Romano C Beacuteneacute DMaxwell 2014b A common analytical model for resilience measurementcausal framework and methodological options Food Security InformationNetwork (FSIN) Technical Series No 2 World Food Programme Rome
Coulthard S 2011 More than just access to 1047297sh the pros and cons of 1047297sherparticipation
in
a
customary
marine
tenure
(Padu)
system
under
pressure
MarPolicy 35 405ndash412
DFID 2011 De1047297ning Disaster Resilience A DFID Approach Paper Department forInternational Development London pp 20
Dercon S Hoddinott J Woldehanna T 2005 Shocks and consumption in 15ethiopian
villages
1999ndash2004
J
Afr
Econ
14
(4)
559ndash585Dercon S 1996 Risk crop choice and savings evidence from Tanzania Econ Dev
Cult Change 44 (3) 485ndash513Duit A Galaz V Eckerberg K 2010 Governance complexity and resilience Glob
Environ Change 20 (3) 363ndash368Eriksen
SEH
Silva
JA
2009
The
vulnerability
context
of
a
savannah
area
inMozambique household drought coping strategies and responses to economicchange Environ Sci Policy 12 (1) 33ndash52
Fafchamps M Lund S 2003 Risk-Sharing networks in rural Philippines J DevEcon 71 (2) 261ndash287
Frankenberger T Nelson S 2013 Background Paper for the Expert Consultation onResilience
Measurement
for
Food
Security
TANGO
International
Rome
Foodand Agricultural Organization and World Food Program
Heltberg R Siegel PS Jorgensen SL 2009 Addressing human vulnerability toclimate change towards a
lsquono-regretsrsquo approach Glob Environ Change 19 89ndash99
Hoddinott
J
Dercon
S
Krishnan
P
2009
Networks
and
informal
mutual
supportin 15 ethiopian villages a description In Kirsten JF Dorward AR Poulton CVink N (Eds) Institutional Economics Perspectives on African AgriculturalDevelopment International Food Policy Research Institute Washington DC pp273ndash286
Hoddinott
J
2006
Shocks
and
their
consequences
across
and
within
households
inRural Zimbabwe J Dev Stud 42 (2) 301ndash321
Intergovernmental Panel on Climate Change (IPCC) 2012 In Field CB Barros VStocker TF Qin D Dokken DJ Ebi KL Mastrandrea MD Mach KJPlattner G-K Allen SK Tignor MMidgley PM (Eds) Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation A SpecialReport of Working Groups I and II of the Intergovernmental Panel on ClimateChange Cambridge University Press Cambridge UK
Jackson T 2005 Motivating sustainable consumptionmdasha review of evidence onconsumer behaviour and behavioural change A Report to the Sustainable
Event type (Vietnam) Reduce
expenditures
Borrow
money
Reduce
Food
Change
1047297shing
strategy
Get
support
Increase
1047297shing
effort
Diversi1047297cation Seek new
collaboration
Migration Exit the
1047297shery
Sell
assets
Total
Others (aggregated) 4 7 4 6 3 0 1 3 0 0 2 30
Erosion 2 4 2 1 6 2 2 2 3 1 25
Catch reduced
suddenly
8 4 6 7 1 2 4 2 34
Gears lost 10 18 6 5 1 2 1 43
Cold wind prolongs 15 7 11 3 1 7 2 46
Typhoon
12
11
10
2
4
2
3
5
4
1
1
55
Illness
11 14
6
2
11
2
2
4
1
1
2
56Food price increase 20 17 19 2 8 5 1 72
Input price increase
continuously
47 39 33 21 40 5 6 16 1 208
Big boats compete
ground and catch
54 39 32 40 9 19 11 15 8 3 2 232
Catch
reduced
continuously
102
70
80
63
22
51
51
25
23
17
6
510
Total 285 230 209 152 105 91 87 75 39 23 15 1311
C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170 169
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
Development Research Network Centre for Environmental StrategiesUniversity of Surrey
Jones L Boyd E 2011 Exploring social barriers to adaptation insights fromWestern Nepal Glob Environ Change 21 (4) 1262ndash1274
Kallstrom HN Ljung M 2005 Social sustainability and collaborative learningAmbio 34 376ndash382
Kelty R Kelty R 2011 Human dimensions of a 1047297shery at a crossroads resourcevaluation identity and way of life in a seasonal 1047297shing community Soc NatResour
24
(4)
334ndash348Klein RJT Nicholls RJ Thomalla F 2003 Resilience to natural hazards how
useful is this concept Environ Hazards 5 35ndash45
Krosnick
JA
Fabrigar
LR
1997
Designing
rating
scales
for
effective
measurementin surveys In Lyberg L Biemer P Collins M de Leeuw E Dippo C SchwarzN
Trewin
D
(Eds)
Survey
Measurement
and
Process
Quality
John
Wiley
andSons Inc New York NY pp 141ndash164
Leichenko R OrsquoBrien K 2008 Environmental Change and Globalization DoubleExposures Oxford University Press New York
Marschke M Berkes F 2006 Exploring Strategies that build livelihood resiliencea case from Cambodia Ecol Soc 11 (1) httpwwwecologyandsocietyorgvol11iss1art42
McGregor JA Cam1047297eld L Woodcock A 2009 Needs wants and goals wellbeingquality
of
life
and
public
policy
Appl
Res
Qual
Life
4
135ndash154McGregor JA 1994 Village credit and the reproduction of poverty in rural
Bangladesh In Acheson J (Ed) Economic Anthropology and the NewInstitutional Economics University Press of AmericaSociety for EconomicAnthropology Washington pp 261ndash281 (Chapter)
McGregor
JA
2011
Reimagining
development
through
the
crisis
watch
initiative
IDS Bull 42 (5) 17ndash23McLaughlin P Dietz T 2007 Structureagency and environment toward an
integrated perspective on vulnerability Glob Environ Change 39 (4) 99ndash111Meyer MA 2013 Social capital and resilience in the context of disaster social
capital
and
collective
ef 1047297cacy
for
disaster
resilience
connecting
individualswith communities and vulnerability with resilience in hurricane-pronecommunities in Florida PhD Dissertation Department of sociology Coloradostate University Fort Collins Colorado (311 p)
Mills DJ Adhuri D Phillips M Ravikumar B Padiyar AP 2011 Shocks recoverytrajectories and resilience among aquaculture-dependent households in post-tsunami
Aceh
Indonesia
Local
Environ
Int
J
Justice
Sustain
16
(5)
425ndash444Morduch J 1995 Income smoothing and consumption smoothing J Econ
Perspect 9 (3) 103ndash114Morris S Carletto C Hoddinott J Christiaensen L 2000 J Epidemiol Commun
Health 54 381ndash387Myers
RA
Worm
B
2003
Rapid
worldwide
depletion
of
predatory 1047297sh
communities Nature 423 280ndash283Nakagawa Y Shaw R 2004 Social capital a missing link to disaster recovery Int J
Mass
Emerg
Disasters
22
(1)
5ndash
34Nussbaum MC 2001 Adaptive preferences and womenrsquos options Econ Philos 1767ndash88
Oslashstergaard N Reenberg A 2010 Cultural barriers to climate change adaptation acase study from Northern Burkina Faso Glob Environ Change 20 (1) 142ndash152
OrsquoBrien K Leichenko R 2000 Double exposure assessing the impacts of climatechange within the context of economic globalization Glob Environ Change 10221ndash232
OrsquoBrien K Eriksen S Sygna L Naess LO 2006 Questioning complacencyclimate change impacts vulnerability and adaptation in Norway AMBIO JHum Environ 35 (2) 50ndash56
OrsquoBrien K Quilan T Ziervogel G 2009 Vulnerability interventions in the contextof multiple stressors lessons from the Southern Africa vulnerability initiative(SAVI) Environ Sci Policy 12 23ndash32
OrsquoRiordan T Jordan A 1999 Institutions climate change and cultural theorytowards a common analytical framework Glob Environ Change 9 (2) 81ndash93
Pain A Levine S 2012 A conceptual analysis of livelihoods and resilienceaddressing the
lsquoinsecurity of agency HPG Working Paper OverseasDevelopment Institute Humanitarian Policy Group London
Pauly D Christensen V Dalsgaard Froese JR Torres F 1998 Fishing downmarine food webs Science 279 (5352) 860ndash863
Pelling M Manuel-Navarrete D 2011 From resilience to transformation theadaptive cycle in two Mexican urban centersEcol Soc 16 (2)11 (online) httpwwwecologyandsocietyorgvol16iss2art11
Prowse
M
Scott
L
2008
Assets
and
adaptation
an
emerging
debate
IDS
Bull
39(4) 42ndash52
Putzel J 1997 Accounting for the lsquodark sidersquo of social capital reading Robert
Putnam
on
democracy
J
Int
Dev
9
(7)
939ndash949
Quinn CH Ziervogel G Taylor A Takama T Thomalla F 2011 Coping withmultiple
stresses
in
rural
South
Africa
Ecol
Soc
16
(3)
doihttpdxdoiorg105751ES-04216-160302
Reid P Vogel C 2006 Living and responding to multiple stressors in South Africamdashglimpses from KwaZulu-Natal Glob Environ Change 16 (2) 195ndash206
Roncoli C Ingram K Kirshen P 2001 The costs and risks of coping with droughtlivelihood
impacts
and
farmersrsquo
responses
in
Burkina
Faso
Clim
Res
19
119ndash132
Schwarz AM Beacuteneacute C Bennett G Boso D Hilly Z Paul C Posala R Sibiti SAndrew N 2011 Vulnerability and resilience of rural remote communities toshocks and global changes empirical analysis from the Solomon Islands GlobEnviron Change 21 1128ndash1140
Sinha
S
Lipton
M
Yaqub
S
2002
Poverty
and
damaging 1047298uctuations
how
dothey relate J Asian Afr Stud 37 (2) 186ndash243
Tansey J OrsquoRiordan T 1999 Cultural theory and risk a review Health Risk Soc 171ndash90
Teschl M Comim F 2005 Adaptive preferences and capabilities somepreliminary
conceptual
explorations
Rev
Soc
Econ
63
(2)
229ndash247
Trimble M Johnson D 2013 Artisanal 1047297shing as an undesirable way of life Theimplications for governance of 1047297shersrsquo wellbeing aspirations in coastal Uruguayand southeastern Brazil Mar Policy 37 37ndash44
Turner BL Kasperson RE Matson P McCarthy JJ Corell RW Christensen LEckley
N
Kasperson
JX
Luers
A
Martello
ML
Polsky
C
Pulsipher
ASchiller A 2003 A framework for vulnerability analysis in sustainabilityscience Proc Natl Acad Sci 100 (14) 8074ndash8079
Vigderhous G 1977 The level of measurement and
lsquoPermissiblersquo statistical analysisin social research Pac Sociol Rev 20 (1) 61ndash72
WFP 2013 Building Resilience Through Asset Creation Resilience and PreventionUnit
Policy
Programme
and
Innovation
Division
World
Food
Program
Rome(23 p)
Walker B Carpenter S Anderies J Abel N Cumming GS Janssen M Lebel LN J Peterson GD Pritchard R 2002 Resilience management in social-ecological systems a working hypothesis for a participatory approach ConservEcol
6
(1)
14Weber EU 2010 What shapes perceptions of climate change Clim Change 1 (3)
332ndash342
Wolf
J
Adger
WN
Lorenzoni
I
Abrahamson
V
Raine
R
2010
Social
capitalindividual responses to heat waves and climate change adaptation an empiricalstudy
of
two
UK
cities
Glob
Environ
Change
20
44ndash52Wood G 2003 Staying secure staying poor the Faustian bargain World Dev 31
(3) 455ndash471World Bank 2011 Building Resilience and Opportunities World Bankrsquos Social
Protection and Labour Strategy 2012ndash2022 World Bank Washington DCYamano T Alderman H Christiaensen L 2003 Child Growth Shocks and Food
Aid in Rural Ethiopia World Bank Washington DCZimmerman F Carter M 2003 Asset smoothing consumption smoothing and the
reproduction of inequality under risk and subsistence constraints J Dev Econ71 233ndash260
von Grebmer K Headey D Beacuteneacute C Haddad L et al 2013 Global Hunger IndexThe Challenge of Hunger Building Resilience to Achieve Food and NutritionSecurity Welthungerhilfe International Food Policy Research Institute andConcern Worldwide Bonn Washington DC and Dublin
170 C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
disaster resilience National Disaster Resilience Roundtable Report 20September 2012 Melbourne Australia 36 p
Adger NW Dessai S Goulden M Hulme M Lorenzoni I Nelson DR Naess LO Wolf J Wreford A 2009 Are there social limits to adaptation to climatechange
Clim
Change
93
335ndash354Adger WN 2003 Social capital collective action and adaptation to climate
change Econ Geogr 79 (4) 387ndash404Adger WN 2006 Vulnerability Glob Environ Change 16 268ndash281Aldrich D 2010 Fixing recovery social capital in post-Crisis resilience J Homeland
Secur 6 1ndash10Ayers
J
Forsyth
T
2009
Community-based
adaptation
to
climate
changestrengthening resilience through development Environment 51 23ndash31
Beacuteneacute C Tew1047297k A 2001 Fishing effort allocation and 1047297shermenrsquos decision-makingprocess in a multi-species small-scale 1047297shery analysis of the conch and lobster1047297shery in Turks and Caicos Islands Hum Ecol 29 (2) 157ndash186
Beacuteneacute
C
Evans
L
Mills
D
Ovie
S
Raji
A
Ta1047297da
A
Kodio
A
Sinaba
F
Morand
PLemoalle J Andrew N 2011 Testing resilience thinking in a poverty contextexperience from the Niger river basin Glob Environ Change 21 (4) 1173ndash1184
Beacuteneacute C Godfrey-Wood R Newsham A Davies M2012 Resilience new utopia ornew tyranny
ndash Re1047298ection about the potentials and limits of the concept of
resilience
in
relation
to
vulnerability
reduction
programmes
IDS
Working
Paperno 405 Institute of Development Studies Brighton 61 p
Beacuteneacute C Newsham A Davies M Ulrichs M Godfrey-Wood R 2014 Resiliencepoverty and development J Int Dev 26 598ndash623
Beacuteneacute C Waid J Jackson-deGraffenried M Begum A Chowdhury M Skarin VRahman A Islam N Mamnun N Mainuddin K Shah MA 2015a Impact of climate-related
shocks
and
stresses
on
nutrition
and
food
security
in
ruralBangladesh Dhaka World Food Programme 119 p
Beacuteneacute C Frankenberger T Nelson S 2015b Design monitoring and evaluation of resilience interventions conceptual and empirical considerations IDS WorkingPaper no459 Institute of Development Studies 23 p
Beacuteneacute
C
2013
Towards
a
quanti1047297able
measure
of
resilience
IDS
Working
Paper
434Institute of Development Studies Brighton 27 p
Bandura A 1977 Self-ef 1047297cacy toward a unifying theory of behavioral changePsychol Rev 84 191ndash215
Baulch R Hoddinott J 2000 Economic mobility and poverty dynamics indeveloping countries J Dev Stud 36 (6) 1ndash23
Belhabib
D
Sumaila
UR
Pauly
D
2015
Feeding
the
poor
contribution
of
WestAfrican 1047297sheries to employment and food security Ocean Coast Manage 11172ndash81
Berkes F Folke C 1998 Linking social and ecological systems for resilience andsustainability In Berkes F Folke C (Eds) Linking Social and EcologicalSystems Management Practices and Social Mechanisms for Building ResilienceCambridge University Press Cambridge pp 1ndash25
Bernier Q Meinzen-Dick R 2014 Resilience and social capital Building Resiliencefor Food and Nutrition Security Conference Paper No 4 International FoodPolicy Research Institute Washington DC 26 p
Bhattamishra R Barrett C 2010 Community-Based risk managementarrangements a review World Dev 38 (7) 923ndash932
Boarini R Kolev A McGregor JA 2014 Measuring well-being and progress incountries at different stages of development towards a more universalconceptual framework OECD Working Paper No 235 Organisation forEconomic Co-operation and Development Development Center
ndash Better Life
Initiative Paris 59 p
Boyd E Osbahr H Ericksen P Tompkins E Carmen Lemos M Miller F 2008Resilience and
lsquoclimatizingrsquo development examples and policy implicationsDevelopment 51 390ndash396
Cam1047297eld
L
McGregor
JA
2005
Resilience
and
wellbeing
in
developing
countriesIn Ungar M (Ed) Handbook for Working with Children and Youth Pathwaysto Resilience Across Cultures and Contexts Sage Publications Thousand OaksCA
Cam1047297eld
L
Ruta
D
2007
Translation
is
not
enough
using
the
Global
PersonGenerated Index (GPGI) to assess individual quality of life in BangladeshThailand and Ethiopia Qual Life 16 (6) 1039ndash1051
Carter M Little P Mogues T Negatu W 2007 Poverty traps and natural disastersin Ethiopia and Honduras World Dev 35 (5) 835ndash856
Cleaver
F
2005
The
inequality
of
social
capital
and
the
reproduction
of
chronicpoverty World Dev 33 (6) 893ndash906
Constas M Frankenberger T Hoddinott J 2014a Resilience measurementprinciples toward an agenda for measurement design Resilience MeasurementTechnical Working Group Technical Series No 1 Food Security informationNetwork Rome
Constas MT Frankenberger J Hoddinott N Mock D Romano C Beacuteneacute DMaxwell 2014b A common analytical model for resilience measurementcausal framework and methodological options Food Security InformationNetwork (FSIN) Technical Series No 2 World Food Programme Rome
Coulthard S 2011 More than just access to 1047297sh the pros and cons of 1047297sherparticipation
in
a
customary
marine
tenure
(Padu)
system
under
pressure
MarPolicy 35 405ndash412
DFID 2011 De1047297ning Disaster Resilience A DFID Approach Paper Department forInternational Development London pp 20
Dercon S Hoddinott J Woldehanna T 2005 Shocks and consumption in 15ethiopian
villages
1999ndash2004
J
Afr
Econ
14
(4)
559ndash585Dercon S 1996 Risk crop choice and savings evidence from Tanzania Econ Dev
Cult Change 44 (3) 485ndash513Duit A Galaz V Eckerberg K 2010 Governance complexity and resilience Glob
Environ Change 20 (3) 363ndash368Eriksen
SEH
Silva
JA
2009
The
vulnerability
context
of
a
savannah
area
inMozambique household drought coping strategies and responses to economicchange Environ Sci Policy 12 (1) 33ndash52
Fafchamps M Lund S 2003 Risk-Sharing networks in rural Philippines J DevEcon 71 (2) 261ndash287
Frankenberger T Nelson S 2013 Background Paper for the Expert Consultation onResilience
Measurement
for
Food
Security
TANGO
International
Rome
Foodand Agricultural Organization and World Food Program
Heltberg R Siegel PS Jorgensen SL 2009 Addressing human vulnerability toclimate change towards a
lsquono-regretsrsquo approach Glob Environ Change 19 89ndash99
Hoddinott
J
Dercon
S
Krishnan
P
2009
Networks
and
informal
mutual
supportin 15 ethiopian villages a description In Kirsten JF Dorward AR Poulton CVink N (Eds) Institutional Economics Perspectives on African AgriculturalDevelopment International Food Policy Research Institute Washington DC pp273ndash286
Hoddinott
J
2006
Shocks
and
their
consequences
across
and
within
households
inRural Zimbabwe J Dev Stud 42 (2) 301ndash321
Intergovernmental Panel on Climate Change (IPCC) 2012 In Field CB Barros VStocker TF Qin D Dokken DJ Ebi KL Mastrandrea MD Mach KJPlattner G-K Allen SK Tignor MMidgley PM (Eds) Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation A SpecialReport of Working Groups I and II of the Intergovernmental Panel on ClimateChange Cambridge University Press Cambridge UK
Jackson T 2005 Motivating sustainable consumptionmdasha review of evidence onconsumer behaviour and behavioural change A Report to the Sustainable
Event type (Vietnam) Reduce
expenditures
Borrow
money
Reduce
Food
Change
1047297shing
strategy
Get
support
Increase
1047297shing
effort
Diversi1047297cation Seek new
collaboration
Migration Exit the
1047297shery
Sell
assets
Total
Others (aggregated) 4 7 4 6 3 0 1 3 0 0 2 30
Erosion 2 4 2 1 6 2 2 2 3 1 25
Catch reduced
suddenly
8 4 6 7 1 2 4 2 34
Gears lost 10 18 6 5 1 2 1 43
Cold wind prolongs 15 7 11 3 1 7 2 46
Typhoon
12
11
10
2
4
2
3
5
4
1
1
55
Illness
11 14
6
2
11
2
2
4
1
1
2
56Food price increase 20 17 19 2 8 5 1 72
Input price increase
continuously
47 39 33 21 40 5 6 16 1 208
Big boats compete
ground and catch
54 39 32 40 9 19 11 15 8 3 2 232
Catch
reduced
continuously
102
70
80
63
22
51
51
25
23
17
6
510
Total 285 230 209 152 105 91 87 75 39 23 15 1311
C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170 169
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
Development Research Network Centre for Environmental StrategiesUniversity of Surrey
Jones L Boyd E 2011 Exploring social barriers to adaptation insights fromWestern Nepal Glob Environ Change 21 (4) 1262ndash1274
Kallstrom HN Ljung M 2005 Social sustainability and collaborative learningAmbio 34 376ndash382
Kelty R Kelty R 2011 Human dimensions of a 1047297shery at a crossroads resourcevaluation identity and way of life in a seasonal 1047297shing community Soc NatResour
24
(4)
334ndash348Klein RJT Nicholls RJ Thomalla F 2003 Resilience to natural hazards how
useful is this concept Environ Hazards 5 35ndash45
Krosnick
JA
Fabrigar
LR
1997
Designing
rating
scales
for
effective
measurementin surveys In Lyberg L Biemer P Collins M de Leeuw E Dippo C SchwarzN
Trewin
D
(Eds)
Survey
Measurement
and
Process
Quality
John
Wiley
andSons Inc New York NY pp 141ndash164
Leichenko R OrsquoBrien K 2008 Environmental Change and Globalization DoubleExposures Oxford University Press New York
Marschke M Berkes F 2006 Exploring Strategies that build livelihood resiliencea case from Cambodia Ecol Soc 11 (1) httpwwwecologyandsocietyorgvol11iss1art42
McGregor JA Cam1047297eld L Woodcock A 2009 Needs wants and goals wellbeingquality
of
life
and
public
policy
Appl
Res
Qual
Life
4
135ndash154McGregor JA 1994 Village credit and the reproduction of poverty in rural
Bangladesh In Acheson J (Ed) Economic Anthropology and the NewInstitutional Economics University Press of AmericaSociety for EconomicAnthropology Washington pp 261ndash281 (Chapter)
McGregor
JA
2011
Reimagining
development
through
the
crisis
watch
initiative
IDS Bull 42 (5) 17ndash23McLaughlin P Dietz T 2007 Structureagency and environment toward an
integrated perspective on vulnerability Glob Environ Change 39 (4) 99ndash111Meyer MA 2013 Social capital and resilience in the context of disaster social
capital
and
collective
ef 1047297cacy
for
disaster
resilience
connecting
individualswith communities and vulnerability with resilience in hurricane-pronecommunities in Florida PhD Dissertation Department of sociology Coloradostate University Fort Collins Colorado (311 p)
Mills DJ Adhuri D Phillips M Ravikumar B Padiyar AP 2011 Shocks recoverytrajectories and resilience among aquaculture-dependent households in post-tsunami
Aceh
Indonesia
Local
Environ
Int
J
Justice
Sustain
16
(5)
425ndash444Morduch J 1995 Income smoothing and consumption smoothing J Econ
Perspect 9 (3) 103ndash114Morris S Carletto C Hoddinott J Christiaensen L 2000 J Epidemiol Commun
Health 54 381ndash387Myers
RA
Worm
B
2003
Rapid
worldwide
depletion
of
predatory 1047297sh
communities Nature 423 280ndash283Nakagawa Y Shaw R 2004 Social capital a missing link to disaster recovery Int J
Mass
Emerg
Disasters
22
(1)
5ndash
34Nussbaum MC 2001 Adaptive preferences and womenrsquos options Econ Philos 1767ndash88
Oslashstergaard N Reenberg A 2010 Cultural barriers to climate change adaptation acase study from Northern Burkina Faso Glob Environ Change 20 (1) 142ndash152
OrsquoBrien K Leichenko R 2000 Double exposure assessing the impacts of climatechange within the context of economic globalization Glob Environ Change 10221ndash232
OrsquoBrien K Eriksen S Sygna L Naess LO 2006 Questioning complacencyclimate change impacts vulnerability and adaptation in Norway AMBIO JHum Environ 35 (2) 50ndash56
OrsquoBrien K Quilan T Ziervogel G 2009 Vulnerability interventions in the contextof multiple stressors lessons from the Southern Africa vulnerability initiative(SAVI) Environ Sci Policy 12 23ndash32
OrsquoRiordan T Jordan A 1999 Institutions climate change and cultural theorytowards a common analytical framework Glob Environ Change 9 (2) 81ndash93
Pain A Levine S 2012 A conceptual analysis of livelihoods and resilienceaddressing the
lsquoinsecurity of agency HPG Working Paper OverseasDevelopment Institute Humanitarian Policy Group London
Pauly D Christensen V Dalsgaard Froese JR Torres F 1998 Fishing downmarine food webs Science 279 (5352) 860ndash863
Pelling M Manuel-Navarrete D 2011 From resilience to transformation theadaptive cycle in two Mexican urban centersEcol Soc 16 (2)11 (online) httpwwwecologyandsocietyorgvol16iss2art11
Prowse
M
Scott
L
2008
Assets
and
adaptation
an
emerging
debate
IDS
Bull
39(4) 42ndash52
Putzel J 1997 Accounting for the lsquodark sidersquo of social capital reading Robert
Putnam
on
democracy
J
Int
Dev
9
(7)
939ndash949
Quinn CH Ziervogel G Taylor A Takama T Thomalla F 2011 Coping withmultiple
stresses
in
rural
South
Africa
Ecol
Soc
16
(3)
doihttpdxdoiorg105751ES-04216-160302
Reid P Vogel C 2006 Living and responding to multiple stressors in South Africamdashglimpses from KwaZulu-Natal Glob Environ Change 16 (2) 195ndash206
Roncoli C Ingram K Kirshen P 2001 The costs and risks of coping with droughtlivelihood
impacts
and
farmersrsquo
responses
in
Burkina
Faso
Clim
Res
19
119ndash132
Schwarz AM Beacuteneacute C Bennett G Boso D Hilly Z Paul C Posala R Sibiti SAndrew N 2011 Vulnerability and resilience of rural remote communities toshocks and global changes empirical analysis from the Solomon Islands GlobEnviron Change 21 1128ndash1140
Sinha
S
Lipton
M
Yaqub
S
2002
Poverty
and
damaging 1047298uctuations
how
dothey relate J Asian Afr Stud 37 (2) 186ndash243
Tansey J OrsquoRiordan T 1999 Cultural theory and risk a review Health Risk Soc 171ndash90
Teschl M Comim F 2005 Adaptive preferences and capabilities somepreliminary
conceptual
explorations
Rev
Soc
Econ
63
(2)
229ndash247
Trimble M Johnson D 2013 Artisanal 1047297shing as an undesirable way of life Theimplications for governance of 1047297shersrsquo wellbeing aspirations in coastal Uruguayand southeastern Brazil Mar Policy 37 37ndash44
Turner BL Kasperson RE Matson P McCarthy JJ Corell RW Christensen LEckley
N
Kasperson
JX
Luers
A
Martello
ML
Polsky
C
Pulsipher
ASchiller A 2003 A framework for vulnerability analysis in sustainabilityscience Proc Natl Acad Sci 100 (14) 8074ndash8079
Vigderhous G 1977 The level of measurement and
lsquoPermissiblersquo statistical analysisin social research Pac Sociol Rev 20 (1) 61ndash72
WFP 2013 Building Resilience Through Asset Creation Resilience and PreventionUnit
Policy
Programme
and
Innovation
Division
World
Food
Program
Rome(23 p)
Walker B Carpenter S Anderies J Abel N Cumming GS Janssen M Lebel LN J Peterson GD Pritchard R 2002 Resilience management in social-ecological systems a working hypothesis for a participatory approach ConservEcol
6
(1)
14Weber EU 2010 What shapes perceptions of climate change Clim Change 1 (3)
332ndash342
Wolf
J
Adger
WN
Lorenzoni
I
Abrahamson
V
Raine
R
2010
Social
capitalindividual responses to heat waves and climate change adaptation an empiricalstudy
of
two
UK
cities
Glob
Environ
Change
20
44ndash52Wood G 2003 Staying secure staying poor the Faustian bargain World Dev 31
(3) 455ndash471World Bank 2011 Building Resilience and Opportunities World Bankrsquos Social
Protection and Labour Strategy 2012ndash2022 World Bank Washington DCYamano T Alderman H Christiaensen L 2003 Child Growth Shocks and Food
Aid in Rural Ethiopia World Bank Washington DCZimmerman F Carter M 2003 Asset smoothing consumption smoothing and the
reproduction of inequality under risk and subsistence constraints J Dev Econ71 233ndash260
von Grebmer K Headey D Beacuteneacute C Haddad L et al 2013 Global Hunger IndexThe Challenge of Hunger Building Resilience to Achieve Food and NutritionSecurity Welthungerhilfe International Food Policy Research Institute andConcern Worldwide Bonn Washington DC and Dublin
170 C Beacuteneacute et al Global Environmental Change 38 (2016) 153ndash170
8182019 Is resilience socially constructed Empirical evidence from Fiji Ghana Sri Lanka and Vietnam
Development Research Network Centre for Environmental StrategiesUniversity of Surrey
Jones L Boyd E 2011 Exploring social barriers to adaptation insights fromWestern Nepal Glob Environ Change 21 (4) 1262ndash1274
Kallstrom HN Ljung M 2005 Social sustainability and collaborative learningAmbio 34 376ndash382
Kelty R Kelty R 2011 Human dimensions of a 1047297shery at a crossroads resourcevaluation identity and way of life in a seasonal 1047297shing community Soc NatResour
24
(4)
334ndash348Klein RJT Nicholls RJ Thomalla F 2003 Resilience to natural hazards how
useful is this concept Environ Hazards 5 35ndash45
Krosnick
JA
Fabrigar
LR
1997
Designing
rating
scales
for
effective
measurementin surveys In Lyberg L Biemer P Collins M de Leeuw E Dippo C SchwarzN
Trewin
D
(Eds)
Survey
Measurement
and
Process
Quality
John
Wiley
andSons Inc New York NY pp 141ndash164
Leichenko R OrsquoBrien K 2008 Environmental Change and Globalization DoubleExposures Oxford University Press New York
Marschke M Berkes F 2006 Exploring Strategies that build livelihood resiliencea case from Cambodia Ecol Soc 11 (1) httpwwwecologyandsocietyorgvol11iss1art42
McGregor JA Cam1047297eld L Woodcock A 2009 Needs wants and goals wellbeingquality
of
life
and
public
policy
Appl
Res
Qual
Life
4
135ndash154McGregor JA 1994 Village credit and the reproduction of poverty in rural
Bangladesh In Acheson J (Ed) Economic Anthropology and the NewInstitutional Economics University Press of AmericaSociety for EconomicAnthropology Washington pp 261ndash281 (Chapter)
McGregor
JA
2011
Reimagining
development
through
the
crisis
watch
initiative
IDS Bull 42 (5) 17ndash23McLaughlin P Dietz T 2007 Structureagency and environment toward an
integrated perspective on vulnerability Glob Environ Change 39 (4) 99ndash111Meyer MA 2013 Social capital and resilience in the context of disaster social
capital
and
collective
ef 1047297cacy
for
disaster
resilience
connecting
individualswith communities and vulnerability with resilience in hurricane-pronecommunities in Florida PhD Dissertation Department of sociology Coloradostate University Fort Collins Colorado (311 p)
Mills DJ Adhuri D Phillips M Ravikumar B Padiyar AP 2011 Shocks recoverytrajectories and resilience among aquaculture-dependent households in post-tsunami
Aceh
Indonesia
Local
Environ
Int
J
Justice
Sustain
16
(5)
425ndash444Morduch J 1995 Income smoothing and consumption smoothing J Econ
Perspect 9 (3) 103ndash114Morris S Carletto C Hoddinott J Christiaensen L 2000 J Epidemiol Commun
Health 54 381ndash387Myers
RA
Worm
B
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Rapid
worldwide
depletion
of
predatory 1047297sh
communities Nature 423 280ndash283Nakagawa Y Shaw R 2004 Social capital a missing link to disaster recovery Int J
Mass
Emerg
Disasters
22
(1)
5ndash
34Nussbaum MC 2001 Adaptive preferences and womenrsquos options Econ Philos 1767ndash88
Oslashstergaard N Reenberg A 2010 Cultural barriers to climate change adaptation acase study from Northern Burkina Faso Glob Environ Change 20 (1) 142ndash152
OrsquoBrien K Leichenko R 2000 Double exposure assessing the impacts of climatechange within the context of economic globalization Glob Environ Change 10221ndash232
OrsquoBrien K Eriksen S Sygna L Naess LO 2006 Questioning complacencyclimate change impacts vulnerability and adaptation in Norway AMBIO JHum Environ 35 (2) 50ndash56
OrsquoBrien K Quilan T Ziervogel G 2009 Vulnerability interventions in the contextof multiple stressors lessons from the Southern Africa vulnerability initiative(SAVI) Environ Sci Policy 12 23ndash32
OrsquoRiordan T Jordan A 1999 Institutions climate change and cultural theorytowards a common analytical framework Glob Environ Change 9 (2) 81ndash93
Pain A Levine S 2012 A conceptual analysis of livelihoods and resilienceaddressing the
lsquoinsecurity of agency HPG Working Paper OverseasDevelopment Institute Humanitarian Policy Group London
Pauly D Christensen V Dalsgaard Froese JR Torres F 1998 Fishing downmarine food webs Science 279 (5352) 860ndash863
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Assets
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Putnam
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Dev
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Quinn CH Ziervogel G Taylor A Takama T Thomalla F 2011 Coping withmultiple
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South
Africa
Ecol
Soc
16
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doihttpdxdoiorg105751ES-04216-160302
Reid P Vogel C 2006 Living and responding to multiple stressors in South Africamdashglimpses from KwaZulu-Natal Glob Environ Change 16 (2) 195ndash206
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Faso
Clim
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Yaqub
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2002
Poverty
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